Social Influence and Information Evaluation in the Digital Age

Social Influence and
Information evaluation
SELECTIVE EXPOSURE TO INFORMATION AND USERS INTERACTION
LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN
THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES
1

Context
The combination of Web-based self-publication and social media
requires new skills to evaluate information
This is the main challenge of information literacy
Relevance, cognitive authority can’t be the main criteria in an
environment defined by social interactions
2

“Social media”: what does it mean?
It is not social networking
It is much more to do with what people are doing with the technology than the
technology itself, for rather than merely retrieving information, users are now
creating and consuming it, and hence adding value to the websites that permit
them to do so
(Campbell et al., 2011, p. 87)
A group of internet-based applications that build on the ideological and the
technological foundations of Web 2.0, and that allow the creation and exchange
of User Generated Content
(Kaplan and Haenlein, 2010, p. 61)
3

Information evaluation allows
To decide where to begin
To predict which source/system would give me the best information
To select
To accept or reject
To determine whether to use or share the information
4

Making judgments of information
Traditional approach to information evaluation: Identifying a set of criteria
people employ when making judgments of information
Information Quality: Evaluating the values of information in terms of
excellence or truthfulness (Taylor)
Credibility: People’s assessment of whether information is trustworthy
based on their own expertise and knowledge (Rieh)
Cognitive Authority: Influence on one’s thoughts that one would recognize
as proper (Wilson). A credible source even though it did not have any
influence on our thoughts
Trust: Belief about the reliability of, dependability of, and confidence in
person, object, or process (Fogg)
5

Social influence
Hillman and Trier (2013, p. 3) state that social influence “provides a
broad range of concepts to explain how people’s individual actions
are affected by other people as a result of interaction”. This implies
that social influence is a natural process, but can be used by people
or businesses to change a person’s attitude or behavior.
Social influence can be used for positive actions (e.g. creating
awareness for societal problems, promoting new products) and
negative actions (e.g. social hacking, social pressure)
6

Normative social influence
Kelman (1985) is often cited as a fundamental analysis of normative social
influence. This type of social influence explains how individuals are
influenced, based on norms.
Kelman distinguishes three sub-types of normative social influence:
compliance, identification and internalization
Compliance occurs when an individual accepts the opinion of others,
hoping that this would lead to a favorable reaction of others.
Identification means that an individual accepts the opinion of others to
maintain a desired relationship.
Internalization represents the strongest influence and occurs when an
individual accepts and beliefs the opinion of others both in public and
private
7

Informational social influence
Informational social influence is explained by Lee, Shi, Cheung, Lim & Sia
(2011). This type of social influence involves accepting information or
advice from a person who may not have previously been known as a
friend or colleague.
Informational social influence is especially relevant in the context of social
media, in which user-generated content is an important type of
information.
An example of this type of social influence in social media could be a
change in purchasing behavior as a consequence of online customer
reviews of a product. These reviews change the attitudes and beliefs of
customers and thereby influence behavior.
8

Rationale of the study
To better understand social influence effects on information behaviour, we
compare studies on misinformation in social networks to another one,
conducted by one of our doctoral student, Albaraa Altourah, related to
agenda setting in Twitter (can a mass media theory like agenda setting be
applied to Twitter?).
Our question is:
can selective exposure to information both create division (divergence)
between users into groups who follow the same interests without being
interested to the others and also generate convergence in the form of
public opinion or common agenda setting ?
9

Misinformation studies
SOCIAL INFLUENCE AND FRAGMENTATION OF DIGITAL
ENVIRONMENT
10

Background 1
World Economic Forum (WEF Report 2013)
Massive digital misinformation is becoming pervasive in online social media: it
has been listed by the WEF as one of main threats of our society
A french resolution this year
The parliament (The French National Assemby) adopted, a few month ago, a
resolution entitled « Resolution on sciences and progess in the Republic).
It « invites the government to think about pedagogical practices based on
sensible (smart) use of digital technologies, especially information selection
learning that would make easier the difference between knowledge and
opinion without scientific basis
11

Original version
TEXTE ADOPTÉ n° 926
SESSION ORDINAIRE DE 2016-2017 21 février 2017
RÉSOLUTION sur les sciences et le progrès dans la République.
L’Assemblée nationale a adopté la résolution dont la teneur suit :
(…)
9. Invite le Gouvernement à réfléchir à des pratiques pédagogiques fondées sur
l’usage raisonné des technologies numériques, en particulier à l’apprentissage
du tri de l’information qui faciliterait la distinction entre des savoirs établis et
des opinions sans fondement scientifique ;
12

Background 2
Algorithmic-driven solutions have been proposed (Qazvinian V and al.
2011, Ciampaglia GL et al. 2015, Resnick P. 2014, Gupta A. et al. 2014, Dong XL, et al. 2015, ...)
Google tries to develop a trustworthiness score to rank the results of queries
13

Example: Bessi et al. 2016
« we analyze the users behavior exposed to the same contents on different
platforms—i.e. Youtube and Facebook. We focus on Facebook posts linking
Youtube videos reported on Science and Conspiracy pages. We then
compare the users interaction with these videos on both platforms »
« We limit our analysis to Science and Conspiracy for two main reasons:
a) scientific news and conspiracy-like news are two very distinct and
conflicting narratives;
b) scientific pages share the main mission to diffuse scientific knowledge
and rational thinking, while the alternative ones resort to unsubstantiated
rumors. »
14

Data collected
The first category (conspiracy theories) includes the pages that
disseminate alternative, controversial information, often lacking
supporting evidence and frequently advancing conspiracy theories.
The second category (science news) includes the pages that
disseminate scientific information. The third category (trolls)
includes those pages that intentionally disseminate sarcastic false
information on the Web with the aim of mocking the collective
credulity online.
15

Results
« Focusing on the consumptions patterns of YouTube videos posted
on Facebook pages, we compute the Spearman’s rank correlation
coefficients between users’ actions on Facebook posts and the
related YouTube videos. We find strong correlations on how users
like, comment and share videos on Facebook and Youtube. Despite
the different algorithm for content promotion, information
reverberate in a similar way »
16

Similar polarization of Science and Conspiracy
users in Facebook and Youtube according Bessi
et al. 2016
17

« Echo chambers »
“We observe sharply peaked bimodal distributions. Users concentrate
their activity on one of the two narratives. To quantify the degree of
polarization we use the Bimodality Coefficient (BC), and we find that
the BC is very high for both Facebook and YouTube. (…) Content has a
polarizing effect, indeed, users focus on specific types of content and
aggregate in separated groups—echo chambers—independently of
the platform and content promotion algorithm”.
18

Users Polarization on Facebook and Youtube
according Bessi et al. 2014
19

Core concepts
Echo chamber
Filter bubble (Eli Pariser 2011)
Collective intelligence is a myth
20

Issues for Information evaluation
Identification of cognitive biais including:
◦ Confirmation biaises
◦ Representativity biais (Bronner 2017)
◦ And many other biaises that economists and psychologists have already
studied to understand behaviours in financial markets (especially
anomalies)
21

Agenda setting study
SOCIAL INFLUENCE AND PUBLIC OPINION IN SOCIAL NETWORK
ENVIRONMENT
22

Proposed questions
•Are social media be able to build convergence between users and
contribute to shape a public opinion despite the fact of its high
potentiality of causing echo chamber effects?
•Is there an inter-user influence while using social media
platforms?
•Presentation of research findings of one of my doctoral students,
Alabraa Altourah who conducted a study at the end of 2016 about
Twitter

A. Altourath research questions
•How can the agenda setting be understood in the context of Twitter?
◦ What limits or enables issue salience creation and transfer to subsequently lead to the
manifestation of agenda setting effect on Twitter?
◦ What are the practices that instigate issue salience in an extremely diverse media
platform such as Twitter?
◦ How may the agenda setting be defined in a platform that enables audiences to be an
active part in the communication cycle?
•How can the newly constructed meanings of agenda setting help
understanding agenda building within Twitter?
◦ Is the agenda building process on Twitter strongly attached to the socio-cultural
setting where the study took place?
◦ Are there any external factors that contaminate the agenda building process within
Twitter?
24

A. Altourah research design (1)
•Platform study
• Using Twitter analytics tool to identify the manifestation of
agenda setting
• Isolating the agenda setting effects and analyze the conditions
that led to its establishment
• Examining the possible existence of homogenous information
on Twitter that leads to the augmentation of the appearance of
certain news
• Examining the role of cultural setting in hindering or
promoting the agenda setting. Comparison between France
and Koweit

Why Twitter? why France and Kuwait?
•Data may be accessed easily
•Data are available publically
•Data may be researched based on different research settings
•The platform is very popular
•France is one of the top 10 countries in number of Twitter users
(Forbes.com, 2016)
•Kuwait has the highest number of Twitter users per capita globally (one in
three people in Kuwait have a Twitter account) (Forbes.com, 2016)
•The two countries have a fundamentally different socio-political setting

Research design (2)
•Users study
• Identify the elements that leads to the establishment of issue
salience
• Identify the role of users as an active part in the
communication cycle in promoting, hindering or avoiding the
effects of agenda setting
• Examine the socially constructed understanding with respect
to information available on Twitter
• Identify the perceived reliability of information found on
Twitter

Platform study: methodology 1
The first step is executed by analyzing 5 selected Twitter accounts from France
and Kuwait to identify if an issue salience has been created and transferred in
the corresponding cyberspace region.
A period of seven days has been set to collect the tweets of the selected Twitter
account to identify the influencer’s agenda. During the seven days period, two
days were selected as the most applicable days for content analysis, which will
be referred to as the first and the second day of analysis.
The first day of analysis represents the day where the selected users posted the
highest number of tweets in relevance to the week’s average. The second day of
analysis on the other hand refers to the day where the selected users posted the
lowest number of tweets in relevance to the week’s average.
28

Platform study: methodology 2
In both the days of analysis, a content analysis method is applied to
identify the most recurrent keywords in the posted tweets. Once the
keywords are identified, they are researched within the corresponding
cyberspace region three days before and three days after their
introduction to assess whether there is an increment or a decrement in
number of tweets mentioning those keywords. This process aims to
identify the Twitter agenda.
The second step is devoted to investigate the level of homogeneity of
media content between selected users, in each study location. This is
conducted by using the socialbearing.com as to collect three-days worth
of tweets of the selected users then analyzing the data using content
analysis.
29

The selected Twitter accounts
France :
Nicolas Sarkozy (@NicolasSarkozy)
Marine Le Pen (@MLP_officiel)
Jean-Luc Mélenchon (@JLMelenchon)
Najat Belkacem (@najatvb)
Le Monde (@lemondefr)
Kuwait :
Waleed Altabtabie (@altabtabie)
Nasser Alduwailah
(@nasser_duwailah)
Almajlliss (@Almajlliss)
Safaa Alhashem (@safaalhashem)
Faisal Almuslem (@faisalalmuslem)
30

Examples
31

Reuse of keywords
after their first introduction
22-24 August 2016 25-27 August 2016 Change in %
Impôt 2351 3837 +63.2%
Être francais 3129 3882 +24.1%
L’immigration 1100 3487 +217%
L’autorité de l’état 75 1668 +2124%
32

Agenda setting effects exist on Twitter
09-10 September
2016
11-12 September
2016
Change in %
Laïcité 2454 4624 88.40%
Frexit 717 765 6.70%
L’outre-mer 12 442 3583.30%
Droit des femmes 159 1572 888.70%
Keywords comparison before and after First Day of Analysis (Marine Le Pen)
(Number of tweets)

Keywords reuse/tweet category
(Ex:Sarkozy account)
22-24 August 2016 25-27 August 2016
Tweet Retweet Reply Mentions Tweet Retweet Reply Mention
Impôt 1018 1195 138 818 1123
+10.3%
2434
+103.7%
280
+102.9%
1513
+84.9%
Être francais 441 2276 412 1161 1123
+10.3%
1123
+10.3%
1123
+10.3%
1123
+10.3%
L’immigration 131 861 108 384 578
+341.2%
2494
+189.6%
418
+287%
1648
+329.2%
L’autorité de l’état 26 42 7 16 316
+1115.5%
1251
+2878.6%
101
+1342.9%
637
+3881.3%
34

Information on Twitter can be
homogenous (France)
•Twitter account with different political orientation engage in a level of
consistency with respect to tweets they post
•Between the 18th of October 2016 and the 21st of October 2016 the
selected accounts engaged in different topics. However the content
analysis identified similar topics between these accounts:
• Police
• Russie
• Immigration
• CETA (Comprehensive Economic and Trade Agreement)
• Goodyear
• Islam
• US
• Impôt
• Intérêt de la France

The process of agenda building in France
is different than Kuwait
In the Kuwaiti twitter sphere there isn’t any structural attempt to
build an agenda that coincides with pressing matters that are of
high relevancy to the public. Instead, the proposed issues on
Twitter are random, based on the personal political believes and
do not affect the majority of the public.
It is rather an attempt to appeal to a specific political or societal
group. Therefore, the establishment of an agenda and the
increment of discussions pertaining to the issue proposed are
limited (agenda setting effects are less occurring, the
twittersphere is less homogenous)

Social influence
in the Kuwaiti twitter sphere
Twitter accounts in Kuwait are less likely to be influenced by each other’s
with respect to tweets content or by exterior influence source
The Twitter usage in Kuwait may be primarily to support and promote
personal propaganda irrespective what other users are concerned about,
benefiting from their high number of followers and the fact that users in
Kuwait are more likely to use Twitter as their prime source of information
Therefore, the possibility of having an exterior influential entity that might
establish a common agenda among Twitter users in Kuwait is unlikely. The
Kuwaiti culture for long has regarded number of major news sources as
largely biased
37

What is similar: Users are immersed in
the illusion of news selection (user study)
What are the factors that determine your choice of Twitter accounts to
follow? (This question aims to determine the elements of the Twitter account
that encourage users to establish a connection with account i.e. number of
followers, type of content, political orientation etc.)
France: 72% of the participants chose to follow accounts on Twitter because
they are known persons
Kuwait: 54% of the participants chose to follow certain account on Twitter
because they are known persons or subject matter experts
But both France and Kuwait attributed Twitter popularity (number of
followers) as the main variable to determine the person as known or not.

Research Findings
Agenda setting effects can exist on Twitter
Information on Twitter can be homogenous
The process of agenda building in France is different than Kuwait
Users are immersed in the illusion of news selection

Some conclusions
related to political information
When Twitter is the one and primary source of information because
of the lack of trust in other sources of information, we observe that
convergence to common topics is low
Common agenda setting and public opinion shaping in Twitter
depend on the number and the credibility of external information
sources
Information overload is a problem to evaluate information but it is at
the same time a condition (when information quality is good) to
overcome selective information exposure drawbacks
40

Social Influence and Information Evaluation in the Digital Age

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