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Laurence Favier, University Charles De Gaulle – Lille 3: Social Influence and Information Evaluation

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V Międzynarodowa Konferencja Naukowa Nauka o informacji (informacja naukowa) w okresie zmian Innowacyjne usługi informacyjne. Wydział Dziennikarstwa, Informacji i Bibliologii Katedra Informatologii, Uniwersytet Warszawski, Warszawa, 15 – 16 maja 2017

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Laurence Favier, University Charles De Gaulle – Lille 3: Social Influence and Information Evaluation

  1. 1. Social Influence and Information evaluation SELECTIVE EXPOSURE TO INFORMATION AND USERS INTERACTION LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 1
  2. 2. 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 LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 2
  3. 3. “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) LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 3
  4. 4. 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 LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 4
  5. 5. 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) LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 5
  6. 6. 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) LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 6
  7. 7. 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 LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 7
  8. 8. 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. LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 8
  9. 9. 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 ? LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 9
  10. 10. Misinformation studies SOCIAL INFLUENCE AND FRAGMENTATION OF DIGITAL ENVIRONMENT LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 10
  11. 11. 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 LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 11
  12. 12. 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 ; LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 12
  13. 13. 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 LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 13
  14. 14. 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. » LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 14
  15. 15. 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. LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 15
  16. 16. 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 » LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 16
  17. 17. Similar polarization of Science and Conspiracy users in Facebook and Youtube according Bessi et al. 2016 LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 17
  18. 18. « 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”. LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 18
  19. 19. Users Polarization on Facebook and Youtube according Bessi et al. 2014 LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 19
  20. 20. Core concepts Echo chamber Filter bubble (Eli Pariser 2011) Collective intelligence is a myth LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 20
  21. 21. 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) LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 21
  22. 22. Agenda setting study SOCIAL INFLUENCE AND PUBLIC OPINION IN SOCIAL NETWORK ENVIRONMENT LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 22
  23. 23. 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
  24. 24. 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? LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 24
  25. 25. 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
  26. 26. 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
  27. 27. 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
  28. 28. 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. LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 28
  29. 29. 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. LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 29
  30. 30. 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) LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 30
  31. 31. Examples LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 31
  32. 32. 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% LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 32
  33. 33. 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)
  34. 34. 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% LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 34
  35. 35. 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
  36. 36. 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)
  37. 37. 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 LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 37
  38. 38. 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.
  39. 39. 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
  40. 40. 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 LAURENCEFAVIER-THE 4TH INTERNATIONALSCIENTIFICCONFERENCEINFORMATIONSCIENCEIN THE AGE OF CHANGEINNOVATIVEINFORMATIONSERVICES 40

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