CSEP Working Paper-24 February 2022

CSEP Working Paper-24
February 2022

About PRRC
 This paper was published as part of the Property Rights Research
 Consortium (PRRC), and supported by Omidyar Network
 India. PRRC is a network of leading think-tanks and research
 organisations, working to collaborate and drive policy action in
 the field of land, housing and property rights in India.

 Support for this research was generously provided by the
 Omidyar Network. CSEP recognises that the value it provides
 is in its absolute commitment to quality, independence,
 and impact. Activities supported by its donors reflect this
 commitment and the analysis and recommendations found in
 this report are solely determined by the scholar(s).

Copyright © Shishir Gupta, Nandini Agnihotri and Sikim Chakraborty

Centre for Social and Economic Progress (CSEP)
CSEP Research Foundation
6, Dr Jose P. Rizal Marg, Chanakyapuri,
New Delhi - 110021, India

Recommended citation:
Gupta, S; Agnihotri, N; Chakraborty, S. (2022). What Drives Media Reporting? Reader-Interest May be the Key
(CSEP Working Paper 24). New Delhi: Centre for Social and Economic Progress.

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Designed by Mukesh Rawat

WHAT DRIVES MEDIA REPORTING?
 Reader-interest may be the key

 Shishir Gupta
 Senior Fellow & COO
 Centre for Social and Economic Progress
 New Delhi, India

 Nandini Agnihotri
 Research Assistant
 Centre for Social and Economic Progress
 New Delhi, India

 Sikim Chakraborty
 Research Analyst
 Centre for Social and Economic Progress
 New Delhi, India

We are grateful to Amb. Shivshankar Menon (Distinguished Fellow, Centre for Social and Economic Progress)
and Dr. Namita Wahi (Senior Fellow, Centre for Policy Research) for their insightful comments and feedback on
the paper.

We express gratitude to a number of experts and leading practitioners for lending their inputs: George Skaria
(Communications Advisor, Centre for Social and Economic Progress), Kumar Sambhav Shrivastava (Founding
Partner and Project Director, Land Conflict Watch), Mrinali Karthick (Database and Collaborations Lead, Land
Conflict Watch), Nitin Sethi (Partner and Editorial Advisor, Land Conflict Watch), Anand Yagnik (senior lawyer
and activist), Sheela Bhatt (senior journalist), Dr. Kalev Leetaru (creator, The GDELT Project).

We thank Karan Partap Singh Kairon (intern, Centre for Social and Economic Progress) for his assistance, and
acknowledge his contributions to the paper. We would also like to thank Land Conflict Watch for their extensive
data on land conflicts that has formed an integral part of this paper. We thank Dweepobotee Brahma and
Aradhika Menokee for their initial ideation of the paper. Lastly, we offer sincere gratitude to the communications
and design team at CSEP. All the errors that remain in the paper are entirely ours.

Table of Contents

Executive Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Literature Review. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Approach and Methodology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

 Occurrence of Conflicts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

 Media Reporting of Conflicts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Key Findings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

 Case Study 1: COVID-19 Oxygen Availability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

 Case Study 2: Farm Bills Protests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Concluding Remarks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Appendix 1: List of 58 unique conflicts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Appendix 2: Unique sources per conflict . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Appendix 3: Twitter data extraction and filtering. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Lists of figures and tables

Figure 1: The two pathways of our study. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Figure 2: Wide disparity between location of occurrence and location of reporting. . . . . . . . . . . . 13

Figure 3: Urban conflicts are much smaller in scale, yet garner significantly more coverage. . . . . 15

Figure 4: Delhi accounted for an inordinately high share of total tweets.. . . . . . . . . . . . . . . . . . . . . 24

Figure 5: Number of tweets saw a spike when the movement launched towards Delhi. . . . . . . . . . 25

Table 1: Disaggregation of 58 conflicts as per region and actors involved. . . . . . . . . . . . . . . . . . . . . 13

Table 2: Total tweets containing keyword ‘oxygen’; total tweets containing ‘oxygen’ and ‘Delhi’ for

each given date.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

What Drives Media Reporting?
 Reader-interest may be the key

Executive Summary
Media plays an important role in informing and shaping public opinion around major issues.
Amartya Sen has argued that “it is not likely that India can have a famine even in years of great food
problems. The government cannot afford to fail to take prompt action when large-scale starvation
threatens. Newspapers play an important part in this, in making the facts known and forcing the
challenge to be faced” (Sen, 1981, p.84, as cited in Besley & Burgess, 2002, p.24). Besley & Burgess
(2002) further put forth that Indian states that have a higher newspaper circulation perform better
in terms of providing calamity relief and distributing food under the Public Distribution System.
Media, thus, has the ability to impact large-scale outcomes through its reportage. This, then, begs the
question: how does the media decide which issues to raise?

The answer commonly veers from the media picking sensational topics to ideological inclinations of
the media houses to covert or overt pressure from stakeholders like the government, businesses, and
communities. The demand side—what the readers prefer and want to read—is largely missing in
this narrative. Being a competitive and profit-making industry, the demand dynamics play a pivotal
role in deciding what gets covered by the media, and what issues get more space than others.

There is a significant and persistent trust deficit between the people and the media in India; only 38%
Indians trust most news, compared to 65% in Finland, 54% in Brazil, 50% in Thailand, and 43% in
Australia (Aneez, Neyazi, Kalogeropoulos, & Nielsen, 2021). Low trust is usually ascribed to media
bias. This conclusion comes naturally for a country where close to 70% of media revenue comes from
advertisements and 30% from reader subscriptions (The Hindu, 2021).

Focussing on the English media, using land conflicts involving Focussing on the English media,
communities1 as the focal point, and comparing the occurrence using land conflicts involving
of conflicts vis-à-vis coverage, we argue that media reporting communities as the focal point,
is linked to reader interest. Reader interest, in turn, is driven and comparing the occurrence
by the location of the conflict and of the reader, the intensity of conflicts vis-à-vis coverage,
of the conflict, and the involvement of a known entity (person, we argue that media reporting is
corporation, etc). The argument is not that reporting may not linked to reader interest. Reader
be ‘influenced’ or ‘sensationalised’, but instead that there are interest, in turn, is driven by the
other, more objective reasons2 as well which play a key role in location of the conflict and of
deciding coverage. This is a crucial finding, helping reinforce the reader, the intensity of the
faith in the institution of the fourth estate which is critical conflict, and the involvement
for a well-functioning democracy, while at the same time of a known entity (person,
highlighting the need for introspection and caution. corporation, etc).

We gauge the location of 7143 ongoing land conflicts involving communities tracked by Land Conflict
Watch (2021). We find that conflicts occurring in rural areas account for more than two-thirds of the
total. This seems intuitive, since larger conflicts involving communities most likely pertain to issues
such as land acquisition, and these are more likely to occur in rural areas than in areas that are already
urbanised. However, when we turn our gaze to the location of the conflicts reported in the media, we
see the opposite. Leveraging arguably the world’s most comprehensive database4 monitoring news
media, we derive a list of 58 land conflicts that are covered by the media5 and find that 39 of these 58
conflicts are located in urban areas. Thus, while rural areas account for 70% of the actual occurrence
of land conflicts, the media reports nearly 67% of such conflicts from urban centres.

1
  Community conflicts are defined as those where at least one party involved is a community of people.
2
  From the media’s point of view. That is, reasons that will continue to affect media reporting even without other potential
 sources of bias such as ideology/ influence.
3
  These conflicts are a subset of the total ongoing conflicts reported by LCW (779 at the time of reference). We use these 714
 since there exists a clear rural-urban location demarcation for these.
4
  Global Database of Events, Language, and Tone (GDELT).
5
  Reported between 2015 and 2019.

 5

What Drives Media Reporting?
Reader-interest may be the key

Not only is the frequency of media reporting on urban We deep-dive into seven of the 58
conflicts greater, but each urban conflict is also covered conflicts and find that the four rural
much more extensively than those in rural areas; this is conflicts in our sample are about
despite the fact that a much larger number of people are 15-20 times as large as the three
potentially impacted in the latter. We deep-dive into seven urban conflicts in terms of the
of the 58 conflicts and find that the four rural conflicts number of people affected, and yet,
in our sample are about 15-20 times as large as the three they garner about 20% less media
urban conflicts in terms of the number of people affected, attention as compared to the latter.
and yet, they garner about 20% less media attention as
compared to the latter.

It is natural to question the reasons for this apparent disconnect. We argue that this may be
happening since a majority of the 40 million English newspaper readers reside in metropolitan
centres, whereas the 470 million readers of regional newspapers are largely concentrated in smaller
towns and rural areas (Kumar & Sarma, 2015). For example, The Times of India, Hindustan Times,
and The Mumbai Mirror are the three most widely read dailies in Mumbai; however, the most widely
read dailies in all of Maharashtra are three regional newspapers, Lokmat, Daily Sakal, and Pudhari
(Media Research Users Council India, 2019). Since a majority of the readership of the English-
language media is centred in and around urban areas, covering issues occurring in close proximity
to the readers’ surroundings is of more importance to them than conflicts that may be much bigger
in scale, but unfolding in a distant, rural setting.

We go on to test our framework of reader interest driving coverage by applying it to other platforms
and issues and find that the framework holds up to the test. We scrape data from the Twitter handles
of nine6 prominent media houses for two recent crises, the COVID-19 oxygen crisis and the protests
in response to the passing of the three ‘Farm Bills’. During the second wave of the pandemic in India
from March to July, 2021, several fault lines such as inadequate provisions of medical-grade oxygen
came to light. We find that of all the scraped tweets mentioning ‘oxygen’ during this time, Delhi’s
share was about 30%. Considering that Delhi accounts for about 1% of India’s population (Office of
the Registrar General & Census Commissioner, 2011), a 30% share seems inordinately high.

The paper has two main conclusions. First, reader interest plays a key role in shaping coverage. Second,
what readers want to consume may or may not be in consonance with reality and with what needs
more urgent redressal from a larger, country-wide perspective. For example, by highlighting Delhi’s
oxygen shortage, the media exerted its influence and pressure to force a response from policymakers.
However, an improvement in Delhi’s oxygen situation may not necessarily have reflected a pan-India
improvement of the crisis, which is what the tweeting pattern would appear to suggest. In a sense,
the system was let off the hook by the media once the crisis neared resolution in Delhi, even though
scrutiny of public health management should have continued until the problem was fully addressed
for the entire country. This may have been sub-optimal from a societal perspective. It is, thus, a tough
balancing act for the media industry—how to stay profitable by giving people what they demand,
while simultaneously covering information that people ought to know.

These findings serve as a timely wake-up call for policymakers not to rely only on English-media
coverage as a means of staying informed about the key issues facing the country, given its urban
skew. How and what the media reports have a significant bearing on how people perceive the world
around them. More research and deliberation are, thus, required to understand media reporting
and assess its potential impact in order for policy discourse to thrive. Strengthening this key pillar of
accountability that upholds the fundamentals of democracy is all the more vital in the present age.

6
  Hindustan Times, PIB India, Press Trust of India, The Indian Express, The Hindu, The Quint, The Telegraph, The Times of
 India, The Wire.

6

What Drives Media Reporting?
 Reader-interest may be the key

Introduction
Land, especially in and around urban centres, is a scarce resource in India. This scarcity is reflected
in abnormally high property prices in big cities. In 2019, Mumbai’s price-to-income7 ratio was 39,
the fifth-highest in Asia, Delhi’s was 15.8, while the ratio was 21.56 for Singapore (Numbeo, 2019).
The limited supply-high price equilibrium in land markets needs to change if we are to grow faster
and lift people out of poverty in the near term (McKinsey Global Institute, 2020).

There are multiple reasons for this sub-optimal equilibrium, key among them being the lack of
clearly defined and documented property rights, coupled with weak administrative and judicial
capacity to resolve conflicts. Consequently, land disputes account for a substantive proportion of
cases in Indian courts—25% of all cases decided by the Supreme Court, and 66% of all civil cases
in India are related to land or property disputes (Wahi, 2019). Additionally, “the average pendency
of a land acquisition dispute, from creation of the dispute to resolution by the Supreme Court, is 20
years” (Wahi, 2019, p. 1). Thus, poorly defined titles and rights, and poorly enforced property rights
lead to a higher frequency of conflicts, and each individual conflict is prolonged due to delays in
conflict resolution (Wahi, 2019).

Given the significance and scale of land-related conflicts, the media8 is instrumental in informing
and shaping public opinion around land-related issues. It shapes discourse primarily through its
discretion in choosing what to report, and the frequency with which it covers each issue. This brings
us to the fundamental question—how does the media decide what to report?9 Studies of this nature
are inherently complex because they require independent information on ‘reality/occurrence’ of
conflicts as well as ‘media coverage’ of similar conflicts to be able to compare and contrast the two,
see if there exists a disparity between the two, and study the drivers of this disparity.

In this paper, we study exactly these two pathways, of reality and media reporting; and attempt to
evaluate the existence and causes of a possible wedge between the two. Focussing on the English
media, using land conflicts involving communities10 as the focal point, and comparing the occurrence
of conflicts vis-à-vis their coverage, we argue that media reporting is linked to reader interest.
Reader interest, in turn, is driven by the location of the conflict and the reader, the intensity of the
conflict, and the involvement of a known entity (person, corporation, etc). We test the veracity of
our framework by analysing and scraping data from the Twitter handles of nine11 prominent media
houses for two recent crises, the COVID-19 oxygen crisis and the protests in response to the three
‘Farm Bills’, and found the framework to be robust.

7
  ‘Price’ refers to median apartment prices in the city. ‘Income’ refers to median familial disposable income. Sourced from
 Numbeo, which is a global, crowd-sourced database that gives information on the cost of living in different cities.
8
  Media refers to English-language media, unless otherwise stated.
9
  Since we are interested in exploring media coverage of land conflicts given they have a significant role in growth and
 development of the country, our focus is only on large conflicts that involve communities of people, as opposed to millions
 of property feuds between families and businesses that are languishing in the courts.
10
  Community conflicts are defined as those where at least one party involved is a community of people.
11
  Hindustan Times, PIB India, Press Trust of India, The Indian Express, The Hindu, The Quint, The Telegraph, The Times of
 India, The Wire.

 7

What Drives Media Reporting?
Reader-interest may be the key

 Figure 1: The two pathways of our study, and the datasets used for each.

 Occurrence of Conflicts Media Reporting of Conflicts
 Urban-rural breakdown Urban-rural breakdown of media
 of land conflicts affecting reporting and the frequency of
 communities of people. reporting on different categories
 of conflicts.

 Global Database of
 Land Conflict Watch (LCW) Events, Language and
 Compiles information on all Tone (GDELT)
 ongoing land conflicts that Indicator of media reporting.
 involve communities Records news reporting from
 around the world on over
 300 categories of events.

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What Drives Media Reporting?
 Reader-interest may be the key

Literature Review
The socio-political power of the media is a widely studied subject that has given rise to a rich body of
work. The relationship between the media and public opinion can be studied through the three inter-
connected lenses of agenda-setting, priming, and framing (Scheufele & Tewksbury, 2007). Agenda
setting refers to the capacity of the media to use its reach to raise public awareness and concern.
By extensively covering a particular issue, the media gives it salience and nudges the public to use
it as a criterion for evaluating public policy. This power to establish points of reference is termed
priming. Agenda-setting and priming often go hand in hand. By making some issues more salient in
people’s minds, the media can influence and shape people’s judgments (Moy, Tewksbury, & Rinke,
2016). Media’s third lever of influence, framing, draws on the media’s control over perspectives it
chooses to highlight or omit. Iyengar and Simon (1993) call attention to the role played by the media
in the First Gulf War. They state that intensive news coverage of the war pushed it to become the
principal issue in American consciousness. This dominance resulted in foreign policy becoming the
key standard by which the public assessed their president.

In their very forceful paper, Mullainathan & Shleifer (2002) argue that there are two primary axes,
‘ideology’ and ‘spin’, which determine what a particular media outlet decides to report. While the
former reflects the agency’s ideological leaning, the latter is driven by an urge to create a more
memorable or sensational story, since it may sell more. The paper shows that in a competitive
industry, ideological differences give rise to media outlets aligned to different ideologies, thus
creating a level playing field for all views to be propagated, even though the underlying news agencies
may be biased towards particular ideologies. However, when it comes to sensational stories bereft of
ideological differences, this competition creates an inducement to spin stories.

Through its primary function of information dissemination, the media informs people of their socio-
political surroundings. Having a more informed electorate strengthens incentives for governments
to be responsive to the needs of vulnerable citizens (Besley & Burgess, 2002). Besley & Burgess
(2002) put forth, using a panel data for states in India, that the states that have a higher newspaper
circulation and an accountable electorate perform better in terms of providing calamity relief and
distributing food under the Public Distribution System.

The media’s role as an agenda-setter, primer, and framer extends to land-based conflicts as well.
Putnam and Shoemaker’s (2007) study of a dispute over land-use rights in Texas, USA, demonstrates
how the media uses priming and framing to set the parameters of a conflict. Due and Riggs (2010)
point to a similar trend in how the non-indigenous media reports land-titling conflicts involving
the native population in Australia. They compare the media’s initial framing, which is holistic and
context-based, to the pro-development narrative used when reporting contractual disagreements
between native titleholders and businesses. Tang and Cote (2020) illustrate how the media’s
agenda-setting and framing decisions determine the outcome of land-based conflicts. They use
evidence from China to show that protests which received a steady commentary framed from a
pro-protestor point of view were more likely to achieve their goals and beat back State acquisition.

In India, a combination of lack of titling and documentation, poorly defined land rights (particularly
land-use versus ownership rights for communities such as indigenous groups), weak administration,
and an overwhelmed judiciary have made contract enforcement extremely difficult and a seemingly
everlasting problem (Wahi, 2019). Given the stage of India’s economic development, this weak
institutional architecture implies a dire need for a mechanism to act as a watchdog, and to ensure
that relevant conflicts are highlighted so that decision-making can happen in a relatively transparent
manner. This makes the role of media even more powerful in a country like India.

 9

What Drives Media Reporting?
Reader-interest may be the key

Approach and Methodology
We first analyse the occurrence of ongoing land-related conflicts that involve communities.
Thereafter, we focus on media reporting of conflicts and the actual content of news reports. These
two pathways form the structural frame of this study. The plinth of our organisational framework
comprises two datasets that are the primary tools of the aforementioned pathways. These two
distinct sources are—Land Conflict Watch (LCW), used to estimate the occurrence of conflicts,
and the Global Database of Events, Language, and Tone (GDELT), used to understand the nature of
media reporting. In this section, we define these sources and elaborate on how we extracted relevant
details from them.

Occurrence of Conflicts
We needed a dataset to understand the geographic disaggregation of conflicts that affect groups of
people than smaller conflicts involving individual differences. The dataset of conflicts from Land
Conflict Watch serves this purpose perfectly. A land conflict as per LCW data is defined as any
instance in which the use of, access to, and/or control over land and its associated resources are
contested by two or more parties, one of which has to be a community (Worsdell & Shrivastava,
2020). Therefore, LCW is indicative of all those ongoing land conflicts that affect communities and
are greater in magnitude than conflicts of a personal nature. These conflicts are categorically not
of a private nature (Worsdell & Shrivastava, 2020), and usually involve subject matters such as the
acquisition of land, that may have a larger impact on the broader development of the country. We
look at 714 ongoing conflicts from LCW and study their regional demarcation which is already pre-
defined in the dataset. We choose to study only 714 despite there being 779 ongoing conflicts at the
time of reference since these 714 have a clearly stated urban-rural specification.

Media Reporting of Conflicts
We use the GDELT Events Database to study media reporting and coverage; in particular we use
the GDELT Global Knowledge Graph (GKG). We study media reporting for events that occurred
between 2015 and 2019.12

GDELT is a platform that monitors the digital news media from nearly every corner of the world in
print, broadcast, and web formats, in over 100 languages (The GDELT Project: Intro, 2020). It records
each event with its corresponding news report as a separate entry, thus forming a comprehensive
compendium of news reports released in any given timeframe. These include information on the
location of the event, details of actors involved, and the number of sources that have reported on
the said event (within the first 15 minutes of its occurrence), among others. GKG is an upgrade on
the GDELT Events Database and it provides more data fields for study as well as a higher volume of
data. It expands GDELT’s capabilities by capturing additional, more latent dimensions that the latter
does not include (The GDELT Project, 2015).

Events in the dataset are categorised into a pre-defined set of 300 categories i.e. Event Codes, ranging
from acts of cooperation to acts of conflict. The characteristics of actors and the location of the event
are also assigned codes. This categorisation follows the Conflict and Mediation Event Observations
Event and Actor Codebook (CAMEO) format (Schrodt, 2012).

  Data starts from 2015, which defines our starting year. We stop reference year at 2019, since 2020 onwards reporting is
12

 concentrated around COVID-19.

10

What Drives Media Reporting?
 Reader-interest may be the key

Since property rights are of primary interest to us, we use data that indicate a violation of property
rights and the onset of a property-related conflict. This data are categorised under the following
three Event Codes (Schrodt, 2012):

171: Seize or damage property. Use of force against property or violation of property rights not
otherwise specified.

1711: Confiscate property. Use force to take control of somebody else’s property, confiscate, expropriate.

1712: Destroy property. Use force to destroy, demolish property.

Filtering for these three Event Codes gave us a list of 9,000 entries, spread across the same or different
conflicts. Then, in order to get a list of events and reports most closely associated with our objective,
we further filtered this dataset based on the Themes13 variable. From a list of 4000-odd pre-defined
themes, we picked 14 that we found most suitable.14 The dataset after the themes-based filtering was
a smaller and more targeted subset of the previous data, comprising approximately 1200 entries.15

We then removed irrelevant and duplicate entries to arrive at a final list of 58 unique conflicts (see
appendix 1). We assigned the relevant entries into single conflicts if they shared the same initial
trigger. That is to say, if the origin of their contention could be traced to a common happening, then
they were deemed a part of the same conflict. Our list of 58 conflicts was dependent on two factors.
First, on media reporting itself. Given that the dataset (GDELT GKG) recorded information only
through news and media sources, this list recorded those conflicts that were covered by the media
at some level. Second, the news reports covering the conflict were recorded in the dataset—some
conflicts may have been covered in the media, but if no news reports for the same showed up in
the dataset, it couldn’t make it to our final list. Our list thus derived, while not exhaustive, is an
objective,16 unbiased account of the conflicts that have been reported in the media, and therefore
gives us a bird’s-eye view of how media coverage differs across different categories of conflicts.

Two final steps followed. First, defining the region of conflict. This involved categorising conflicts
into ‘urban’ or ‘rural’ depending on their location of occurrence. Second, defining the actors or
parties involved in the conflict. We assign two parties to each conflict from four self-appointed
labels–State, Community, Individual(s), and Corporate. They are defined as follows:

State: refers to the government and all its arms and organs. This includes governance bodies, the
judiciary, municipal authorities, etc. In our parlance, wherever public land is involved, the party
involved is listed as the State.

Community: refers to a large group of people, collectively affected in the same manner by the
conflict; or collectively perpetrating the conflict.
Individual(s): refers to either a single individual, or a group of persons who may be affected by or
perpetrating a conflict. A distinction between Community and Individual(s) is that the latter refers
to relatively more known people.

Corporate: refers to corporations involved in the conflict.

13
  We used the V2Themes variable.
14
  We include: all Themes with the substring ‘Property’, ‘WB_817_LAND_AND_HOUSING’, ‘WB_2288_LAND_
 ACQUISITION_LAWS’, ‘WB_888_LAND_TENURE’, ‘WB_890_CADASTRE_AND_LAND_REGISTRATION’,
 ‘WB_891_LAND_REFORM’, ‘WB_994_LAND_RECLAMATION’, ‘WB_1721_SPATIAL_PLANNING_AND_LAND_
 USE’, ‘WB_867_CITIES_AND_CONFLICT’, ‘ECON_HOUSING_PRICES’, ‘WB_2186_SOCIAL_HOUSING’, ‘WB_2186_
 RENTAL_HOUSING’, ‘WB_870_HOUSING_CONSTRUCTION’, ‘WB_904_HOUSING_MARKETS’, ‘WB_2957_
 EMINENT_DOMAIN’, ‘WB_699_URBAN_DEVELOPMENT’.
15
  Combination of same events reported in multiple sources, or separate events.
16
 Since not chosen by design

 11

What Drives Media Reporting?
Reader-interest may be the key

Despite being arguably the most comprehensive source in its class and well-suited to get a preliminary
view of reporting, we found that GDELT is perhaps not the best source to examine the frequency
of coverage. As a result, we decided to manually run an exhaustive search on media coverage for a
chosen set of seven conflicts, from the list of 58 unique land conflicts. Each of these seven conflicts
was divided into separate events to the extent possible (provided these events/updates occurred
between 2015 and 2019). The news reporting for each event was explored using the News tab on
the Google search engine. We used specific keywords and their different iterations, along with other
filters such as a customised date range, to get relevant hits on Google. The date range was set to
anywhere between two months to a year, depending on the search requirements for each conflict.
Only news reports related to the conflict or a specific event were recorded. In the event that we got
upwards of 10 pages worth of hits, we stopped recording news reports at page 10. This gave us an
estimate of ‘coverage’, wherein coverage stands for the total number of news reports we found for the
conflict based on our defined search strategy.

Since we have relied on Google as our primary tool for determining the extent of coverage, it is
important to note a few key aspects that are embedded in this strategy. The news reports we got
through our keywords were predominantly in English. The resultant links were largely from a
mix of daily newspapers, periodical publications, and a few online news sources. The reports were
either digital counterparts to print content, or were exclusively written for the online platform. Our
coverage was, thus, largely defined by what was reported online by major17 English dailies.

Key Findings
Analysing and comparing the actual occurrence of land conflicts with what is covered in the media
highlights three key drivers of media reporting—location of the conflict and of the reader, the
parties involved, and the severity of the conflict. On average, urban conflicts are covered more than
rural; those that are more severe in nature get covered more than the rest; and finally, conflicts that
involve some known entity (person, corporation, etc.) tend to be covered more by the media.

While 70% of land conflicts involving communities occur in rural areas, 67% of conflicts
tracked by the media occur in urban areas
As seen in Figure 2, the number of conflicts occurring in rural areas is more than two-thirds of
those conflicts occurring in urban areas. This seems intuitive, since land conflicts pertaining to
issues such as land acquisition are more likely to happen in rural areas than in areas that are already
urbanised. When we look at the location of conflicts reported by the media, we see the opposite
view. As stated earlier, by leveraging GDELT, we come up with a list of 58 land conflicts that are
covered by the media18 (Table 1). This list helps us draw interesting insights about the regional
distribution of and the parties involved in these conflicts.

  For example, we refer to The Hindu and Hindustan Times as major English dailies, among other sources.
17

  Reported between 2015 and 2019.
18

12

What Drives Media Reporting?
 Reader-interest may be the key

Figure 2: Wide disparity between location of occurrence19 and location of reporting.20 While
rural areas account for 70% of the occurrence; in the media, 67% of such conflicts reported are
from urban areas.

 100%

 90%

 80%

 70%

 60%

 50%

 40%
 70%
 30%

 20%
 33%
 10%

 0%
 Occurrence Media Reporting
 Rural Urban

Source: Land Conflict Watch (2021), GDLET GKG (2021).

Table 1: Disaggregation of 58 conflicts as per region and actors involved. Conflicts involving
the State are higher in number than other category of conflicts, so are conflicts occurring in
urban areas.

 Urban Rural21 Total

 State22 and Community23 17 14 31

 Corporate24 and Community 15 4 19

 State and Individual(s)25 7 1 8

 Total 39 19 58

Source: GDELT GKG (2021).

19
  Location of occurrence is mapped for 714 conflicts.
20
  Location of reporting is based on our list of 58 unique conflicts.
21
  ‘Rural’ being inclusive of forest land.
22
  Refers to the government and all its arms and organs. This includes governance bodies, the judiciary, municipal authorities,
 etc. Wherever public land is involved, the party involved is the State.
23
  Refers to a large group of people, collectively affected in the same manner by the conflict; or collectively perpetrating the conflict.
24
  Refers to corporations involved in the conflict. These may be in the form of real estate developers in urban areas,
 corporations running mining plants, etc.
25
  Refers to either a single individual, or a group of persons who may be affected by or perpetrating a conflict. A distinction
 between Community and Individual(s) is that the latter refers to relatively more well-known people.

 13

What Drives Media Reporting?
Reader-interest may be the key

As is clear from Table 1, the maximum number of conflicts involve the State and a community.
The second-largest category is where a community is in conflict with a corporation. And the last
is where individual(s) are in conflict with the State. This list of 58 comprises conflicts of a diverse
nature, they involve political representatives, some of the biggest developers, and developments in
key infrastructure projects, among other stakeholders and issues.

Next, we move to understand the frequency of coverage, that is, how many times a conflict appears
in the media. To do that, we selected seven illustrative examples of conflicts from the larger list of 58
conflicts and did a deep dive into each of these seven. These seven conflicts comprise three urban
conflicts, namely-Alibaug Illegal Structures, Thoothukudi Copper Plant, and Kathputli Colony;
and four rural conflicts-Mumbai-Ahmedabad High-Speed Rail Corridor, Amaravati Capital City,
Manipur Bills, and Forest Rights Acts. They represent different regions26 as well as actors involved
and make for a reliable list to study the coverage differential.

Location of the conflict, the parties involved, and the severity of the conflict drive the
frequency of coverage
Not only does the media cover more urban than rural conflicts, but each urban conflict is also covered
more deeply, that is, there are many more reports on each urban conflict; this is despite the fact that
rural conflicts impact a larger number of people. We also found that the four rural conflicts in our list
of seven were about 15-20 times as large as the three urban conflicts in terms of the number of people
affected, and yet the rural conflicts received about 20% less coverage than the latter.

  Rural or urban, depending on the main geography of the conflict.
26

14

What Drives Media Reporting?
 Reader-interest may be the key

Figure 3: A comparison of the coverage27 received by the seven28 chosen conflicts and their
scale29 i.e., the number of people affected. Urban conflicts are much smaller in scale, yet garner
significantly more coverage.

 85
 80 Thoothukudi Copper
 75 Plant
 70
 65
 60
 55
 Coverage received

 50 Alibaug Illegal Forest Rights Act
 Structures
 45
 40
 35 Kathputli Colony
 30
 25
 Mumbai–Ahmedabad
 20 High Speed Rail
 Amaravati
 15 Corridor
 Manipur Bills
 10
 5
 0
 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7
 Scale of Conflict (log of number of people potentially affected)

 Rural Urban

Source: Land conflict Watch (2021), GDELT GKG (2021), multiple news media sites were referred to understand coverage and scale.

Figure 3 shows a broadly negative relationship between the scale of a conflict and its coverage. Since
rural conflicts involve a significantly larger number of people, this negative relationship indicates
that rural conflicts are covered less, and urban conflicts are covered more. For example, the Manipur
Bills conflict, despite potentially impacting the largest number of people among all seven conflicts,
is covered the least. On the other hand, the Alibaug Illegal Structures conflict is the 3rd most widely
covered, despite impacting a significantly smaller number of people. This urban-rural differential
in coverage notwithstanding, what else drives coverage within urban and rural conflicts? The seven
case studies point to a number of important answers. We break down each of these seven conflicts
into their key discrete events to find what may be driving coverage at a more disaggregated level.

27
  Coverage for each conflict was determined by a targeted search on the Google News tab, as described in the methodology.
28
  We chose these seven from our broader list of 58 unique conflicts, derived from the GDELT GKG database.
29
  We determine the scale of a conflict by estimating the number of people potentially impacted. This number is derived from a
 combination of sources: from the Land Conflict Watch database, and from our reading of multiple news reports on the conflict.

 15

Media coverage of 7 key land-related conflicts
 Event 1
 Conflict Mumbai-Ahmedabad High-Speed Rail Scale (people Unique
 10
 1
 Event 2
 2

 Corridor30 potentially impacted) Sources Event 3
 Coverage
 6 7
 Event 4
 Region: Rural 100,000-120,000 16 26 Event 5
 Parties involved: State, community

 Context: The Mumbai-Ahmedabad High-Speed Rail Corridor, a bullet train line connecting the two
 cities, was announced in 2017. The project has since then faced hindrances in the acquisition of land
 and has been subject to protests by communities in both Gujarat and Maharashtra. Protests have
 occurred on several counts; they largely have to do with challenging the land acquisition process by
 states, unfair compensation, and loss of livelihood of the affected parties.

 Event 1: In 2016, the Gujarat state assembly passed a Bill, i.e. The Right to Fair Compensation and
 Transparency in Land Acquisition, Rehabilitation and Resettlement (Gujarat Amendment) Bill,
 amending the land acquisition laws in the state. The amendments do away with the requirement for a
 Social Impact Assessment report for some projects, and sidesteps the consent clauses for acquisition.

 Event 2: Tribal groups in Maharashtra protested a November 2017 notification by the government
 diluting the power of gram sabhas. As per this change, the sanction of the gram sabhas is not needed by
 the state to acquire tribal land. The protests were held at Azad Maidan in Mumbai, by tribal communities
 who were at risk of losing their land to the Bullet Train project, and other similar projects.
 Event 3: The project received wildlife clearance to continue construction in the Thane Creek Flamingo
 Wildlife Sanctuary and parts of Sanjay Gandhi National Park.
 Event 4: The Maharashtra Regional and Town Planning Act was invoked by the Maharashtra
 government to acquire land from tribal communities in Palgarh district.
 Event 5: The Gujarat High Court in 2019 dismissed around 120 petitions filed by farmers challenging
 the land acquisition process for the project. The process and the amendments in the land acquisition
 law by the state in 2016 were deemed valid by the Court.

  Following words were removed from the word cloud for Mumbai-Ahmedabad High-Speed Rail Corridor as they were redundant: project, Mumbai, Gujarat, Ahmedabad, Thane, state.
30

Conflict Alibaug Illegal Structures Scale (people Unique 31

 potentially impacted) Sources Event 1
 Region: Urban Coverage
 19

 Event 2
 Parties involved: State, individual(s) 600-700 19 50

 Context: A petition was filed by an activist against illegal constructions built along the beach in
 Alibaug, Raigad district. The 160-170 illegal buildings, largely bungalows, were unauthorised and built
 within the low and high tide areas, and were in violation of Maharashtra Coastal Zone Management
 Authority rules.

 Event 1: In response to the said petition, the Bombay High Court ordered the state government to
 demolish illegal constructions built along the beach in Alibaug town of Raigad district.

 Event 2: The state government responded and carried out demolitions of the illegal bungalows. One of
 the bungalows here was of Nirav Modi, and it seems that most of the coverage around the court order
 and the demolition of the illegal structures was driven by Nirav Modi’s involvement.

 Conflict Amaravati Capital City31 Scale (people Unique 23

 Region: Rural potentially impacted) Sources Event 1
 Coverage
 Event 2
 Parties involved: State, community 100,000-110,000 11 3
 26
 Context: Upon the division of erstwhile Andhra Pradesh into two states- Andhra Pradesh and
 Telangana- the former’s government proposed a new state capital at Amaravati. Other than conventional
 land acquisition in exchange for compensation, one of the methods of acquisition employed for this
 project was through a Land Pooling Scheme; the land owners would get ownership of the developed
 land and other benefits as compensation once the capital was ready.
 Event 1: The project ran into problems and faced protests by people who had given up their land for
 this pooling scheme. There was talk of forceful acquisition of land and unfair compensation to farmers.
 Event 2: In 2019, the newly elected state government announced a three-capital idea, a trifurcation
 of the state capital. There was further dissent against the possibility of three capitals and potential
 relocation of the capital from Amaravati to elsewhere.

31
 Following words were removed from the word cloud for Amaravati Capital City as they were redundant: Amaravati, Andhra, Pradesh, state, village

Conflict Thoothukudi Copper Plant32 Scale (people Unique 61
 Event 1
 Region: Urban potentially impacted) Sources 13 Event 2
 190,000-210,000
 Coverage
 Parties involved: Corporate, community 26 79 5 Event 3

 Context: The Sterlite Copper Plant, operated by Sterlite Industries and owned by Vedanta, is located in
 Thoothukudi district, Tamil Nadu. The Plant has often been in the news for violation of environmental
 norms, and reportedly posed hazardous working conditions with multiple workers getting injured in
 the course of their work.

 Event 1: Protests against the Plant intensified in 2018 on several counts. Allegations of negligent working
 conditions continued; a proposed expansion of the Plant was in violation of land and environmental
 regulations. The protest, however, resulted in at least 13 casualties.
 Event 2: Following this, the government’s order for the closure of the Plant was probed by the National
 Green Tribunal. The NGT subsequently ordered the reopening of the Plant in November, 2018.

 Event 3: This decision was later reversed by the Supreme Court in February of 2019, and the Plant
 remained shut.

32
 Following words were removed from the word cloud for Thoothukudi Copper Plant as they were redundant: Thoothukudi, copper, plant, Sterlite, Vedanta.

Event 1
 Conflict Kathputli Colony33 Scale (people Unique
 5
 8 Event 2
 Region: Urban potentially impacted) Sources 13
 Event 3
 Coverage

 Parties involved: State, community 10,000-15,000 12 31
 5
 Event 4

 Context: Residents of Kathputli Colony, an urban slum in New Delhi, were to be temporarily relocated
 while the slum area was redeveloped. While some people relocated to ‘transit camps’, others refused
 citing several reasons- corruption, lack of transparency, and subpar conditions of the transit camps.
 There have also been allegations of forcible evictions by the police. After years of resistance, the slum
 area was razed by the Delhi Development Authority (DDA) to make way for the redevelopment project,
 while several residents had still not been relocated elsewhere.
 Event 1: Residents claimed corruption and unpaid compensation, while the government insisted
 obstruction of development by protestors and those resisting relocation.
 Event 2: The DDA expanded the list of slum residents to be given allocations in the redeveloped
 housing units. Beneficiaries added in the expanded list may be given flats in Rohini; current residents
 in the area protested as they expected the value of their properties to fall due to this move.

 Event 3: The DDA razed a portion of the colony, the High Court initially granted stay on further
 demolitions so that those eligible for rehabilitation may shift, and those who are not may file appeals.
 Protestors continued to insist that they will not relocate to temporary transition camp.
 Event 4: Delhi CM inspected the conditions of the temporary transition camp for relocated dwellers.
 The project was further delayed and residents alleged that transit camp was unlivable and in poor
 condition. The DDA set a 2-month deadline for the residents to vacate the colony, so the redevelopment
 project may continue.

33
 Following words were removed from the word cloud for Kathputli Colony as they were redundant: Kathputli, Delhi, dda, colony, year, families, resident, house.

Conflict Manipur Bills34 Scale (people Unique 6 13 Event 1
 Region: Rural potentially impacted) Sources
 Coverage Event 2
 Parties involved: State, community 2,000,000-3,000,000 14 3
 22 Event 3

 Context: The mass discontent in the state dates back to its 2011 census count. Post agitation by the Meitei
 (valley) community, to introduce an Inner Line Permit system to distinguish between ‘Manipuris’ and
 ‘non-Manipuris’, three Bills were introduced and passed in the legislative assembly. The ‘Hill Tribes’,
 however, did not agree with such a system. This mutual disagreement between the two communities
 has been a major aggravator in this conflict.
 Event 1: In 2015, the aforementioned three Bills were introduced and passed in the Manipur State
 Assembly. These Bills are namely: the Protection of Manipur People's Bill 2015, the Manipur Shops and
 Establishment (Second Amendment) Bill 2015, and the Manipur Land Revenue and Land Reforms
 (Seventh Amendment) Bill 2015. The passage of these Bills amplified discontent and widened the rift
 between communities.
 Event 2: The three Bills potentially altered the rights of tribal communities over land, and the
 classification of residents as ‘natives’ of the state or otherwise, among other things.
 Event 3: Of the protests that followed the passage of the Bills, the most prominent was in Churachandpur,
 Manipur; several people were killed and injured during this protest. It was the Churachandpur protest
 that garnered widespread media attention.

34
 Following words were removed from the word cloud for Manipur Bills as they were redundant: Manipur, state, bill, people, district.

Conflict Forest Rights Act35 Scale (people Unique 27
 Event 1
 Region: Rural potentially impacted) Sources 17
 Coverage Event 2
 Parties involved: State, community 800,000-1,200,000 19 44
 Context: The Forest Rights Act of 2006 is also known as the Scheduled Tribes and Other Traditional
 Forest Dwellers (Recognition of Forest Rights) Act, 2006. It “recognizes the rights of the forest
 dwelling tribal communities and other traditional forest dwellers to forest resources, on which these
 communities were dependent for a variety of needs” (The Forest Rights Act, 2006). In 2008, petitioners
 contended the validity of the Forests Rights Act and pointed out that it has caused deforestation and
 encroachment of forest land. The petitioners demanded the eviction of those whose claims over the
 forest land have been rejected under the law. The Supreme Court subsequently directed the state and
 central governments to file affidavits to show the status of the claims from these tribal members, which
 the governments failed to do.

 Event 1: Following this, the Supreme Court in 2019 directed multiple states to evict those whose claims
 had been rejected.

 Event 2: This order incited reactions from tribal groups across the country, alleging that their claims
 had been unfairly and wrongly rejected. Some states revaluated these claims and looked at them afresh,
 while others filed review petitions against the Court’s order.

35
 Following words were removed from the word cloud for Forest Rights Act as they were redundant: fra, land, Supreme.

What Drives Media Reporting?
Reader-interest may be the key

As the case studies demonstrate, conflicts involving known entities36 are covered more, irrespective
of their role in the conflict. The Alibaug Illegal Structures conflict, for instance, involves people
(presumably) from a certain wealth-based class. The core conflict pertains to the demolition of 160-
170 illegal structures that had been built in violation of environmental norms, but one of the persons
whose bungalow was involved was Nirav Modi—and therefore, a large chunk of coverage was driven
by his name in the headlines. Similarly, the eventual demolition of his property also received a
large share of coverage. The reporting was thus driven by a known name, irrespective of the scale,
severity or most interestingly, the role of that well-known person in the conflict. In stark contrast,
the Kathputli Colony conflict, despite being an urban conflict in the national capital involving many
more people, did not get as much coverage.

The third critical driver of coverage is the severity of the conflict. Among all our conflicts, the
Thoothukudi Copper Plant is covered the most. In addition to being an urban conflict and involving
a known corporation, the third element driving the coverage of this conflict is the fact that 13 people
unfortunately lost their lives protesting against the Plant. This particular event within this conflict
garners the highest share of the coverage. Likewise, in the Manipur Bills conflict, nearly 60% of the
coverage is driven by the third event, where several people were killed at the Churachandpur protests.

While we may argue that the severity of the conflict is a contributing factor for wider coverage, it
does not seem to be uniformly applicable, bringing us back to the potential urban-rural divide. In
contrast to the Copper Plant conflict, the Manipur Bills conflict, affecting the largest number of
people, and where many lives were lost, gets the least coverage in our sample. Comparing Event 3 in
Manipur Bills with Event 1 in Thoothukudi Copper Plant, since they are events of a similar nature,
we see that the latter gets nearly 5 times more coverage, further bringing out the coverage disparity
driven by the location of occurrence, a distinctly felt urban-rural divide.

Media Coverage is Driven by Reader Interest
Ceteris paribus, what drives this seemingly greater media coverage of urban conflicts? Does it reflect
a bias on the part of media, as is usually construed and linked with low trust? Or could there be a
more objective criterion explaining this? Like any other industry, the media covers a combination
of what is important to make known to a wide audience, and what people actually want to read. Our
research, however, indicates that the latter is a crucial driver. The question then becomes, why do
readers want to read certain types of news more than others?

At least a part of the answer lies in understanding who the reader is. The English-language media
reaches about 40 million readers, while the reach of the regional-language media is close to 470
million (Kumar & Sarma, 2015). However, regional languages witness a higher preference in
suburban and rural areas, and the circulation of English and Hindi-language print dailies is largely
confined to big cities. For example, while The Times of India, Hindustan Times, and Mumbai Mirror
are the three most widely read dailies in Mumbai, the most widely read dailies in all of Maharashtra
are three newspapers in regional languages, Lokmat, Daily Sakal, and Pudhari (Media Research
Users Council India, 2019). Similarly, the two biggest English dailies in Chennai are The Times of
India and The Hindu while the three biggest in the state of Tamil Nadu are Daily Thanthi, Dinakaran,
and Dinamalar. The Tamil edition of The Hindu is at the fifth position (Media Research Users
Council India, 2019). Since the bulk of the readership of the English-language media is centred in
and around urban areas, covering issues occurring in close proximity to the readers’ surroundings
is of more importance than conflicts that may be much bigger in scale, but unfolding in a distant,
rural setting.

  Famous people, corporations.
36

22

What Drives Media Reporting?
 Reader-interest may be the key

 Given that higher coverage of urban conflicts is driven by readership preference, a natural question
 arises: does this hold true only for land-related conflicts, or is this true for other kinds of crises as
 well? We answer this question using two case studies of crises not involving land. Here, we analyse
 social media, Twitter in particular, to get our data on media reporting.37

 Case Study 1: COVID-19 Oxygen Availability
 During the second wave of the COVID-19 pandemic in India from March to nearly July, 2021,
 several fault lines came to light. One of these was the shortage of necessary medical provisions in
 hospitals, such as medical-grade oxygen, beds for patients, and medicines. The situation was at its
 worst in April and May, when the rise in the number of COVID-19 cases overwhelmed hospitals.
 The scarcity of available and accessible supply of medical-grade oxygen, in particular, became a
 central issue and one of grave concern. However, the talk on the oxygen crisis seemed to be centred
 around a few metropolitan areas, even though the problem itself was presumably nationwide. In
 order to confirm this and to derive insights, we looked at the Twitter handles of nine38 media houses,
 and scraped their tweets from the beginning of April to the end of May—arguably the worst-hit
 period during the second wave. We filtered the tweets to see how many of them were related to
 the oxygen shortages; another round of filtering gave us tweets about Delhi’s oxygen shortage in
 particular.

 Figure 4: Total count of tweets containing the word ‘oxygen’; and in red, total tweets addressing
 ‘Delhi’ as well as ‘oxygen’. Delhi accounted for an inordinately high share of total tweets.

 320
 Tweets containing the keyword Oxygen

 Tweets containing the keyword Delhi
 in tweets containing the keyword Oxygen
Count of tweets

 240

 160

 80

 0
 2021
 Apr 5
 Apr 6
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 Apr 10
 Apr 11
 Apr 12
 Apr 13
 Apr 14
 Apr 15
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 Apr 18
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 Apr 21
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 Apr 23
 Apr 24
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 Apr 27
 Apr 28
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 Apr 30
 May 1
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 May 13
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 May 15
 May 16
 May 17
 May 18
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 May 20
 May 21
 May 22
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 May 24
 May 25
 May 26
 May 27
 May 28
 May 29

 Source: Twitter handles of Hindustan Times, PIB India, Press Trust of India, The Indian Express, The Hindu, The Quint, The
 Telegraph, The Times of India, The Wire (April 5, 2021 to May 29, 2021).

 37
  Refer to the appendix for methodology on both case studies.
 38
  Hindustan Times, PIB India, Press Trust of India, The Indian Express, The Hindu, The Quint, The Telegraph, The Times of
 India, The Wire.

 23