News for you is not for me: Data-driven Computational Journalism - Panel talk at Algorithmic Personalization and News (APEN18)

1. News for you is not for me:
Data-driven studies on media and
public attention and news consumption
Jisun An
Qatar Computing Research Institute

2. 10 Must-Read news
of the day?

3. Old but brilliant metaphor:
Journalists = Gatekeepers

4. Critical role of news media
• Even in the era of social media, our understanding of the
world is still dominantly shaped by news media.
http://www.journalism.org/2016/07/07/pathways-to-news/
!4

5. Bias in news reporting
• Many kinds of bias in news reporting have been studied.
• Gatekeeping bias (also called selection bias):
• What we see, read, and hear about incidents is a result
of the gatekeeping by the journalists and news media.
• Foreign news coverage reflects the social, economic,
and political relationships among countries.
!5

6. https://www.technologyreview.com/s/532036/data-mining-reveals-how-news-coverage-varies-around-the-world/
!6

7. Two models of the criteria
of news selection
A trustee model
Journalists should give what
audience ought to know
A market model
Journalists should give what
audience want to read

8. In the traditional setting…
A trustee model
Journalists should give what
audience ought to know
A market model

9. In competitive news industry
A trustee model
A market model
Journalists should give what
audience want to read

10. Most-viewed articles Placement of news stories

11. Understanding what people
want to know
• These days journalists are trying to find a balance between
what people ought to know and what people want to know
• For that, it is important to understand what people want to
know. However, it may
• change over time
• be topic-dependent
✓Data on user interests makes it possible to understand what
people want to know in more details.
!11

12. Two studies on understanding
what people want to know
1. Media Attention vs Public Attention
2. News Consumption by Demographics
What We Read, What We Search:
Media Attention and Public Attention Among 193 Countries
WWW 2018
https://dl.acm.org/citation.cfm?id=3186137
Multidimensional Analysis of the News Consumption of Different
Demographic Groups on a Nationwide Scale
SocInfo 2017
https://link.springer.com/chapter/10.1007/978-3-319-67217-5_9

13. 1. Media Attention vs Public Attention
What We Read, What We Search:
Media Attention and Public Attention Among 193
Countries
13

14. Data collection - media attention
• Unfiltered News run by Jigsaw
http://unfiltered.news/ !14
South
Korea
North
Korea
US

15. Data collection - public attention
• Google Trends
Search Term
Origin
Location
Time
!15

16. Build the multiplex network
NM: Media attention network
(from Unfiltered News)
NP: Public attention network
(from Google Trends)
+
!16

17. Afghanistan
Iran
Pakistan
United States of America
Albania
Republic of Macedonia
Algeria
Egypt
France
Iraq
Israel
Libya
Morocco
Russia
Saudi Arabia
SyriaTunisia
Turkey
Yemen
Angola
Brazil
China
Mozambique
Nigeria
Portugal
Anguilla
The Bahamas
Antigua and Barbuda
Barbados
Guyana
Jamaica
North Korea
Trinidad and Tobago
United Kingdom
Argentina
Bolivia
Chile
Colombia
Cuba
Ecuador
Mexico
Peru
Spain
Uruguay
Venezuela
Armenia
Azerbaijan
Georgia
Germany
Australia
Bosnia and Herzegovina
Fiji
New Zealand
Austria
Greece
Italy
Switzerland
Kazakhstan
Turkmenistan
Ukraine
Bahrain
Jordan
Kuwait
Oman
Qatar
United Arab Emirates
Bangladesh
Burma
India
Haiti
Saint Kitts and Nevis
Saint Lucia
Belarus
Belgium
Cameroon
Netherlands
Belize
Guatemala
Taiwan
Benin
Gabon
Gambia
Niger
Panama
Bermuda
Canada
Bhutan
Japan
Croatia
Montenegro
Serbia
Botswana
Namibia
South Africa
Zimbabwe
British Virgin Islands
Brunei
Philippines
South Korea
Bulgaria
Romania
Burkina Faso
Mali
Thailand
Cambodia
Indonesia
Malaysia
Vietnam
Central African Republic
Chad
Senegal
Cayman Islands
Togo
Hong Kong
Costa Rica
Nicaragua
Slovenia
Cyprus
Czech Republic
Slovakia
Dominica
Dominican Republic
Puerto Rico
Sudan
El Salvador
Honduras
Eritrea
Ethiopia
Estonia
Latvia
Kenya
Somalia
Papua New Guinea
Samoa
Tonga
Finland
Norway
Sweden
French Guiana
Martinique
French Polynesia
Sierra Leone
Ghana
Gibraltar
Greenland
Iceland
Guadeloupe
Guam
Guinea
Suriname
Macau
Hungary
Sri Lanka
Singapore
Ireland
Isle of Man
Kyrgyzstan
Tajikistan
Uzbekistan
Rwanda
Tanzania
Uganda
Kiribati
Lithuania
Lebanon
Liberia
Liechtenstein
Poland
Luxembourg
Madagascar
Mauritius
Réunion
Malawi
Zambia
Maldives
Malta
Mauritania
Moldova
Monaco
Montserrat
Nepal
New Caledonia
Paraguay
Burundi
Mayotte
San Marino
Seychelles
Solomon Islands
Swaziland
United States Virgin Islands
B(NM): Media attention
Afghanistan
India
Iran
Pakistan
Turkey
United States of America
Albania
France
Germany
Greece
Italy
United KingdomAlgeria
Egypt
Japan
Morocco
Saudi Arabia
Spain
Syria
Tunisia
Angola
Brazil
Portugal
South Africa
AnguillaBarbados
British Virgin Islands
Canada
Dominica
Dominican Republic
Guyana
Jamaica
Puerto Rico
Saint Kitts and Nevis
Saint Lucia
Trinidad and Tobago
Antigua and Barbuda
Argentina Chile
Colombia
Mexico
Paraguay
Uruguay
Armenia
Azerbaijan
Georgia
Russia
Ukraine
Australia
New Zealand
Austria
Croatia
Switzerland
China
Bahrain
Bangladesh
Kuwait
Philippines
Qatar
United Arab Emirates
Belarus
Lithuania
Poland
Belgium
Netherlands
Belize
Guatemala
Honduras
Benin
Ghana
Nigeria
Togo
Bermuda
Bhutan
Nepal Thailand
Bolivia
Peru
Bosnia and Herzegovina
Montenegro
Serbia
Slovenia
Botswana
Zambia
Zimbabwe
Guadeloupe
Hong Kong
Singapore
United States Virgin Islands
Brunei
Indonesia
Malaysia
Bulgaria
Burkina Faso
Gabon
Mali
Burma
Burundi
Kenya
Rwanda
Tanzania
Uganda
Cambodia
Vietnam
Cameroon
Cayman Islands
Cuba
Central African Republic
Senegal
Chad
Libya
Sudan
Macau
Venezuela
Costa Rica
Nicaragua
Panama
Ecuador
Cyprus
Czech Republic
Slovakia
Haiti
Israel
Lebanon
El Salvador
Eritrea
Ethiopia
Estonia
Finland
Latvia
Norway
Sweden
Somalia
Fiji
French Guiana
Martinique
Suriname
French Polynesia
New Caledonia
Gambia
Guinea
Gibraltar
Greenland
Iceland
Grenada
Guam
South Korea
Hungary
Iraq
Ireland
Isle of Man
Jordan
Oman
Kazakhstan
Uzbekistan
Kiribati
Papua New Guinea
Samoa
Taiwan
Kyrgyzstan
Liberia
Liechtenstein
Luxembourg
Madagascar
Malawi
Maldives
Sri Lanka
Malta
Mauritania
Mauritius
Mayotte
Moldova
Romania
Monaco
Mongolia
Montserrat
Mozambique
Namibia
Niger
Republic of Macedonia
Réunion
San Marino
Yemen
Seychelles
Sierra Leone
Solomon Islands
Swaziland
Tajikistan
The Bahamas
Tonga
Turkmenistan
Turks and Caicos Islands
B(NP): Public attention
!17

18. Centrality of a country in B(NM)
and B(NP) positively correlate
One country gets high media
(public) attention from other
countries, it also gets high public
(media) attention.
!18

19. Dyadic relationships: Top k countries
who get the attention from one country
S.
Korea
US
China
K
Top@1
neighbor
Top@2
neighbors
Media Attention
S.
Korea
Japan
China
K
Top@1
neighbor
Top@2
neighbors
Public Attention

20. Dyadic relationships: Top k countries
who get the attention from one country
S.
Korea
` US
Top@1
neighbor
Media Attention
S.
Korea
Japan
Top@1
neighbor
Public Attention
Overlap of top@1 neighbor of South Korea
between NM and NP is 0.

21. Overlap of top@k neighbors of
each country between NM and NP
In 63.2% of the countries,
the media and the public
pay the most attention
(k=1) to different countries.
Media’s heavy attention to
the United States is
noticeable.
!21
Temporally stable; but
worldwide convergence
can happen.

22. Community structures in B(NM)
and B(NP) by InfoMap [39]
•
‘Global village’ trend in media
attention:
80 countries in one community
Clearer geographical splits
!22

23. Community structures by
InfoMap [39]
The core of civilizations proposed by
Huntington [15] is still observed with
fine-grained interaction patterns
among countries.
!23

24. Media attention
vs Public attention
• Unfiltered News and Google Trends are good data
sources to track media and public attention.
• The media and public attention are often at odds
• The media may be losing the power of agenda setting in the
online era, and the public may be seeking other online sources
to address their media needs.
!24

25. 2. News Consumption by Demographics
Multidimensional Analysis of the News Consumption of
Different Demographic Groups on a Nationwide Scale

26. Daum: the second largest
news portal in South Korea

27. Why Korean news portal?
Requires Social Security Number for
the registration
SSN includes Gender and Age information

28. 10s & Male
10s & Female
20s & Male
20s & Female
The top 30 most
viewed news
articles by different
demographic
groups
Gender
[Male or Female]
Age group
[10s, 20s, 30, 40s, or
50s and above]

30. Beyond the section level:
Four dimensions of news
Section
Topic
Sub-Topic
News Item

31. Middle East Respiratory Syndrome
(MERS) outbreak in South Korea (2015)
186 confirmed patients with a death toll of 36.
16,693 people were quarantined.

32. Four dimensions of news on
MERS outbreak
Middle East Respiratory Syndrome (MERS)
outbreak in South Korea
News
item 1
News
item 2
News
item 3
News
item 4
News
item N
…
Society Politics
Why/how
outbreak
started
Responsibility
of the
government
and/or
president
Economical
impact in
tourism, etc
Reporting
newly
confirmed
patient,
death tolls
Section
Topic
Sub-Topic
News Item

33. Demographic differences in
news consumption
1. Men and women consume news differently.
2. As the age difference increases, the similarity decreases within
same-sex groups.
3. The age differences among male groups are higher than among
female groups.
4. At section and topic levels, news consumption across
demographic groups are similar, but at subtopic and item levels,
their consumptions are difference.
5. A pair of the two groups shares 11.3% of news items in common
on average.

34. Summary
• We introduced the methods on
• Measuring the gap between media and public attention
• Measuring the news consumption differences in four different
news dimensions
• We observed
• News consumption across different demographic groups are
extremely different.
• A huge and consistent gap between media and public attention
exists.

35. 10 Must-Read news of the
day
• What people ought to know and what people want to
know need to be balanced.
• This balance should be importantly considered in
personalization.
• Our methods can be used to measure it.

36. @JisunAn
http://jisun.me
!36