In this study, we explore the effect of diversity among people who share a story about a scientific discovery, on the recipient’s credibility assessment regarding that story. The data used in this study were gathered in two phases. Initial data were collected through the Twitter application program interface. The data were then used in an experimental setting: We manipulated the level of diversity of real-life Twitter followings, supposedly retweeting a story to our participants (n = 274). Each of our participants was then asked to complete a paper-based survey. Our findings show that social diversity can enhance the perceived credibility of a shared item. This effect is amplified among individuals with high digital literacy, as well as individuals with high need for cognition. The study offers a deeper understanding of credibility assessment mechanisms within Twitter and other social networking sites.
AbelJDWirthMO (1977) Newspaper vs. TV credibility for local news. Journalism Quarterly54: 371–375.
2.
AdamsSde BontABergM (2006) Looking for answers, constructing reliability: An exploration into how Dutch patients check web-based medical information. International Journal of Medical Informatics75: 66–72.
3.
Amichai-HamburgerYHayatT (2017) Social networking. The International Encyclopedia of Media Effects, 1–12.
4.
Amichai-HamburgerYFineAGoldsteinA (2004) The impact of Internet interactivity and need for closure on consumer preference. Computers in Human Behavior20: 103–117.
5.
AndersonAABrossardDScheufeleDAXenosMA (2012) Online talk: How exposure to disagreement in online comments affects beliefs in the promise of controversial science. In: PhillipsLCarvalhoADoyleJ (eds) Citizen Voices: Performing Public Participation in Science and Environment Communication. Bristol: Intellect, pp. 119–135.
6.
ArazyOMorganWPattersonR (2006) Wisdom of the crowds: Decentralized knowledge construction in Wikipedia. In: Proceedings of the 16th annual workshop on information technologies & systems (WITS). Phoenix, AZ, 8 December.
7.
BybeeRMcCraeBLaurieR (2009) PISA 2006: An assessment of scientific literacy. Journal of Research in Science Teaching: The Official Journal of the National Association for Research in Science Teaching46: 865–883.
8.
CacioppoJTPettyRE (1982) The need for cognition. Journal of Personality and Social Psychology42: 116.
9.
CentolaDMacyM (2007) Complex contagions and the weakness of long ties. American Journal of Sociology113: 702–734.
10.
CheungCMThadaniDR (2010) The effectiveness of electronic word-of-mouth communication: A literature analysis. In: Proceedings of the 23rd Bled eConference eTrust: implications for the individual, enterprises and society. Available at: https://repository.hkbu.edu.hk/hkbu_staff_publication/4116/
11.
ChildsS (2005) Editorial: Blogging for health. He@lth Information on the Internet45: 1–2.
12.
ClineRJWHaynesKM (2001) Consumer health information seeking on the Internet: The state of the art. Health Education Research16: 671–692.
13.
CohenARStotlandEWolfeDM (1955) An experimental investigation of need for cognition. The Journal of Abnormal and Social Psychology51: 291.
14.
CohenJCohenPWestSGAikenLS (2013) Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. Routledge.
15.
ColemanJSKatzEMenzelH (1966) Medical Innovation: A Diffusion Study. Indianapolis, IN: Bobbs-Merrill Company.
16.
CsardiGNepuszT (2006) The igraph software package for complex network research. Interjournal, Complex Systems1695: 1–9.
17.
DawsonJF (2014) Moderation in management research: What, why, when, and how. Journal of Business and Psychology29: 1–19.
18.
DeshpandeAJadadAR (2006) Web 2.0: Could it help move the health system into the 21st century?The Journal of Men’s Health & Gender3: 332–336.
19.
DholakiaRRSternthalB (1977) Highly credible sources: Persuasive facilitators or persuasive liabilities?Journal of Consumer Research3: 223–232.
20.
DivianiNvan den PutteBGianiSvan WeertJC (2015) Low health literacy and evaluation of online health information: A systematic review of the literature. Journal of Medical Internet Research17: e112.
21.
DivianiNVan den PutteBMeppelinkCSvan WeertJC (2016) Exploring the role of health literacy in the evaluation of online health information: Insights from a mixed-methods study. Patient Education and Counseling99: 1017–1025.
22.
Dvir-GvirsmanS (2017) I like what I see: Studying the influence of popularity cues on attention allocation and news selection. Information, Communication & Society22: 286–305.
FaulFErdfelderEBuchnerALangAG (2009) Statistical power analyses using G* Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods41: 1149–1160.
25.
FlanaginAJMetzgerMJ (2000) Perceptions of Internet information credibility. Journalism & Mass Communication Quarterly77: 515–540.
26.
FlanaginAJMetzgerMJ (2007) The role of site features, user attributes, and information verification behaviors on the perceived credibility of web-based information. New Media & Society9: 319–342.
27.
FoxS (2006) Online Health Search 2006. Washington, DC: Pew Internet & American Life Project.
28.
FreedGLClarkSJButchartATSingerDCDavisMM (2011) Sources and perceived credibility of vaccine-safety information for parents. Pediatrics127: S107–S112.
29.
GottfriedJShearerE (2016) News Use across Social Medial Platforms 2016. Washington, DC: Pew Research Center.
30.
GranovetterMS (1973) The strength of weak ties. American Journal of Sociology78: 1360–1380.
31.
GranovetterMS (1978) Threshold models of collective behavior. American Journal of Sociology83: 1420–1443.
32.
GuilbeaultDBeckerJCentolaD (2017) Complex contagions: A decade in review. Arxiv Preprint Arxiv. Available at: https://arxiv.org/abs/1710.07606
33.
GuntherAC (1992) Biased press or biased public? Attitudes toward media coverage of social groups. Public Opinion Quarterly56: 147–167.
34.
HargittaiE (2005) Survey measures of web-oriented digital literacy. Social Science Computer Review23: 371–379.
35.
HargittaiEFullertonLMenchen-TrevinoEThomasKY (2010) Trust online: Young adults’ evaluation of web content. International Journal of Communication4: 468–494.
36.
HarkinsSGPettyRE (1987) Information utility and the multiple source effect. Journal of Personality and Social Psychology52: 260.
37.
HarrisLDennisC (2011) Engaging customers on Facebook: Challenges for e-retailers. Journal of Consumer Behaviour10: 338–346.
38.
HayatTBraininENeterE (2017a) With some help from my network: Supplementing eHealth literacy with social ties. Journal of Medical Internet Research19: e98.
39.
HayatTHershkovitzAKramerNStephanW (2016a) Credibility assessment and tie strength on Facebook. In: Proceedings of the 17th annual conference of the association of Internet research, Berlin, 5–8 October.
40.
HayatTLesserOSamuel-AzranT (2017b) Gendered discourse patterns on online social networks: A social network analysis perspective. Computers in Human Behavior77: 132–139.
41.
HayatTSamuel-AzranTGalilyY (2016b) Al-Jazeera Sport’s US Twitter followers: Sport-politics nexus?Online Information Review40: 785–797.
42.
HeathCBellCSternbergE (2001) Emotional selection in memes: The case of urban legends. Journal of Personality and Social Psychology81: 1028–1041.
43.
HenwoodFWyattSHartASmithJ (2003) “Ignorance is bliss sometimes”: Constraints on the emergence of the informed patient’in the changing landscapes of health information. Sociology of Health & Illness25: 589–607.
44.
HovlandCIJanisILKelleyHH (1953) Communication and Persuasion; Psychological Studies of Opinion Change. New Haven, CT: Yale University Press.
45.
JohnsonFSbaffiLRowleyJ (2016) Students’ approaches to the evaluation of digital information: Insights from their trust judgments. British Journal of Educational Technology47: 1243–1258.
46.
LeeE-JJangYJ (2010) What do others’ reactions to news on Internet portal sites tell us? Effects of presentation format and readers’ need for cognition on reality perception. Communication Research37: 825–846.
47.
McGuireWJ (1978) An information-processing model of advertising effectiveness. In: DavisHLSilkAJ (eds) Behavioral and Management Science in Marketing. New York, NY: John Wiley & Sons, pp. 156–180.
48.
MarkusML (1987) Toward a “critical mass” theory of interactive media: Universal access, interdependence and diffusion. Communication Research14: 491–511.
49.
MetzgerMJ (2007) Making sense of credibility on the Web: Models for evaluating online information and recommendations for future research. Journal of the Association for Information Science and Technology58: 2078–2091.
50.
MetzgerMJFlanaginAJ (2015) Psychological approaches to credibility assessment online. In: SundarSS (ed.) The Handbook of the Psychology of Communication Technology. New York, NY: John Wiley & Sons, pp. 445–466.
51.
PageSE (2008) The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies. Princeton, NJ: Princeton University Press.
52.
PepeA (2011) The relationship between acquaintanceship and coauthorship in scientific collaboration networks. Journal of the Association for Information Science and Technology62: 2121–2132.
53.
PornpitakpanC (2004) The persuasiveness of source credibility: A critical review of five decades’ evidence. Journal of Applied Social Psychology34: 243–281.
54.
ReichardtJBornholdtS (2006) Statistical mechanics of community detection. Physical Review E74: 016110.
55.
RowleyJJohnsonFSbaffiL (2015) Students’ trust judgements in online health information seeking. Health Informatics Journal21: 316–327.
56.
SalmonCT (1986) Perspectives on involvement in consumer and communication research. Progress in Communication Sciences7: 243–268.
57.
SbaffiLRowleyJ (2017) Trust and credibility in web-based health information: A review and agenda for future research. Journal of Medical Internet Research19: e218.
SherifMHovlandCI (1961) Social Judgment: Assimilation and Contrast Effects in Communication and Attitude Change. Oxford: Yale University Press.
60.
StviliaBMonLYiYJ (2009) A model for online consumer health information quality. Journal of the American Society for Information Science and Technology60: 1781–1791.
61.
SurowieckiJ (2004) The Wisdom of Crowds: Why the Many are Smarter than the Few and How Collective Wisdom Shapes Business, Economies, Societies and Nations. New York, NY: Doubleday, p. 296.
62.
TraagVA (2016) Complex contagion of campaign donations. PloS one11(4): e0153539.
63.
ToplakMEWestRFStanovichKE (2011) The cognitive reflection test as a predictor of performance on heuristics-and-biases tasks. Memory & Cognition39: 1275–1289.
64.
TurcotteJYorkCIrvingJSchollRMPingreeRJ (2015) News recommendations from social media opinion leaders: Effects on media trust and information seeking. Journal of Computer-Mediated Communication20: 520–535.
65.
TutenTLBosnjakM (2001) Understanding differences in web usage: The role of need for cognition and the five factor model of personality. Social Behavior and Personality: An International Journal29: 391–398.
66.
UganderJBackstromLMarlowCKleinbergJ (2012) Structural diversity in social contagion. Proceedings of the National Academy of Sciencesof the United States of America109: 5962–5966.
67.
WeigoldMFergusonMA (1986) Motivation and cognition: Media source diversity and issue domain salience, differentiation and integration. In: Proceedings of the annual meeting of the international communication association, 22–26 May 1986, Chicago, IL.
68.
WejnertB (2002) Integrating models of diffusion of innovations: A conceptual framework. Annual Review of Sociology28: 297–326.
69.
WinterSKrämerNC (2012) Selecting science information in Web 2.0: How source cues, message sidedness, and need for cognition influence users’ exposure to blog posts. Journal of Computer-Mediated Communication18: 80–96.
70.
WinterSKrämerNCRösnerLNeubaumG (2015) Don’t keep it (too) simple: How textual representations of scientific uncertainty affect laypersons’ attitudes. Journal of Language and Social Psychology34: 251–272.
71.
ZhangYBudaR (1999) Moderating effects of need for cognition on responses to positively versus negatively framed advertising messages. Journal of Advertising28: 1–15.
