Seems Legit: An Investigation of the Assessing and Sharing of Unverifiable Messages on Online Social Networks

References

• Agarwal R, Prasad J (1998) A conceptual and operational definition of personal innovativeness in the domain of information technology. Inform. Systems Res. 9(2):204–215.Link, Google Scholar
• Ajzen I, Fishbein M (1980) Understanding Attitudes and Predicting Social Behavior (Prentice-Hall, Englewood Cliffs, NJ).Google Scholar
• Alkhattabi M, Neagu D, Cullen A (2010) Information quality framework for e-learning systems. Knowledge Management E-Learn. Internat. J. 2(4):340–362.Google Scholar
• Alkhattabi M, Neagu D, Cullen A (2011) Assessing information quality of e-learning systems: A web mining approach. Comput. Human Behav. 27(2):862–873.Crossref, Google Scholar
• Allport GW, Postman L (1946) An analysis of rumor. Public Opinion Quart. 10(4):501–517.Crossref, Google Scholar
• Allport GW, Postman LJ (1947) The Psychology of Rumor (Henry Holt and Company, New York).Google Scholar
• Arif A, Robinson JJ, Stanek SA, Fichet ES, Townsend P, Worku Z, Starbird K (2017) A closer look at the self-correcting crowd: Examining corrections in online rumors. Proc. 2017 ACM Conf. Comput. Supported Cooperative Work Soc. Comput. (Association for Computing Machinery, New York), 155–168.Google Scholar
• Arnaboldi V, Conti M, Passarella A, Dunbar RIM (2017) Online social networks and information diffusion: The role of ego networks. Online Soc. Network Media 1:44–55.Crossref, Google Scholar
• Backstrom L, Boldi P, Rosa M, Ugander J, Vigna S (2012) Four degrees of separation. Proc. 4th Annual ACM Web Sci. Conf. (Association for Computing Machinery, New York), 33–42.Google Scholar
• Barki H, Hartwick J (1994) Measuring user participation, user involvement, and user attitude. Management Inform. Systems Quart. 18(1):59–82.Crossref, Google Scholar
• Bayus BL, Jain S, Rao AG (2001) Truth or consequences: An analysis of vaporware and new product announcements. J. Marketing Res. 38(1):3–13.Crossref, Google Scholar
• Berger J, Milkman KL (2012) What makes online content viral? J. Marketing Res. 49(2):192–205.Crossref, Google Scholar
• Biehal GJ, Sheinin DA (2007) The influence of corporate messages on the product portfolio. J. Marketing 71(2):12–25.Crossref, Google Scholar
• Bywaters M, Andrade J, Turpin G (2004) Determinants of the vividness of visual imagery: The effects of delayed recall, stimulus affect and individual differences. Memory 12(4):479–488.Crossref, Google Scholar
• Canter DV, Grieve N, Nicol C, Benneworth K (2003) Narrative plausibility: The impact of sequence and anchoring. Behav. Sci. Law 21(2):251–267.Crossref, Google Scholar
• Chaiken S (1980) Heuristic vs. systematic information processing and the use of source vs. message cues in persuasion. J. Personality Soc. Psych. 39(5):752–766.Crossref, Google Scholar
• Chaiken S, Ledgerwood A (2012) A theory of heuristic and systematic information processing. van Lange PA, Kruglanski W, Higgins ET, eds. Handbook of Theories of Social Psychology, vol. 1 (Sage Publications Ltd, Thousand Oaks, CA), 246–266.Crossref, Google Scholar
• Chaiken S, Maheswaran D (1994) Heuristic processing can bias systematic processing: Effects of source credibility, argument ambiguity, and task importance on attitude judgment. J. Personality Soc. Psych. 66(3):460–473.Crossref, Google Scholar
• Chakravarty A, Liu Y, Mazumdar T (2010) The differential effects of online word-of-mouth and critics’ reviews on pre-release movie evaluation. J. Interactive Marketing 24(3):185–197.Crossref, Google Scholar
• Chau M, Li TMH, Wong PWC, Xu JJ, Yip PSF, Chen H (2020) Finding people with emotional distress in online social media: A design combining machine learning and rule-based classification. Management Inform. Systems Quart. 44(2):933–955.Crossref, Google Scholar
• Chen S, Shechter D, Chaiken S (1996) Getting at the truth or getting along: Accuracy- vs. impression-motivated heuristic and systematic processing. J. Personality Soc. Psych. 71(2):262–275.Crossref, Google Scholar
• Cheung C, Sia CL, Kuan K (2012) Is this review believable? A study of factors affecting the credibility of online consumer reviews from an ELM perspective. J. Assoc. Inform. Systems 13(8):618–635.Google Scholar
• Cohen J (1960) A coefficient of agreement for nominal scales. Ed. Psych. Measurement 20(1):37–46.Crossref, Google Scholar
• Cohn MA, Mehl MR, Pennebaker JW (2004) Linguistic markers of psychological change surrounding September 11, 2001. Psych. Sci. 15(10):687–693.Crossref, Google Scholar
• Connell L, Keane MT (2006) A model of plausibility. Cognitive Sci. 30(1):95–120.Crossref, Google Scholar
• Constant D, Kiesler S, Sproull L (1994) What’s mine is ours, or is it? A study of attitudes about information sharing. Inform. Systems Res. 5(4):400–421.Link, Google Scholar
• Coppersmith G, Dredze M, Harman C (2014) Quantifying mental health signals in Twitter. Proc. Workshop Computational Linguistics Clinical Psych. Linguistic Signal Clinical Reality (Association for Computational Linguistics, Stroudsburg, PA), 51–60.Google Scholar
• Cropanzano R, Mitchell MS (2005) Social exchange theory: An interdisciplinary review. J. Management 31(6):874–900.Crossref, Google Scholar
• Daley DJ, Kendall DG (1964) Epidemics and rumours. Nature 204(4963):1118–1118.Crossref, Google Scholar
• Deci E, Ryan RM (1985) Intrinsic Motivation and Self-Determination in Human Behavior (Plenum, New York).Crossref, Google Scholar
• DeLone WH, McLean ER (1992) Information systems success: The quest for the dependent variable. Inform. Systems Res. 3(1):60–95.Link, Google Scholar
• Dias N, Pennycook G, Rand DG (2020) Emphasizing publishers does not effectively reduce susceptibility to misinformation on social media. Harvard Kennedy School Misinform. Rev. 1(1):1–12.Google Scholar
• DiFonzo N, Bordia P (2007) Rumor Psychology: Social and Organizational Approaches (American Psychological Association, Washington, DC).Crossref, Google Scholar
• DiFonzo N, Bordia P, Rosnow RL (1994) Reining in rumors. Organ. Dynam. 23(1):47–62.Crossref, Google Scholar
• Edwards SM, Gangadharbatla H (2001) The novelty of 3D product presentations online. J. Interactive Advertising 2(1):10–18.Crossref, Google Scholar
• Eliashberg J, Robertson TS (1988) New product preannouncing behavior: A market signaling study. J. Marketing Res. 25(3):282–292.Crossref, Google Scholar
• Fang YH (2014) Beyond the credibility of electronic word of mouth: Exploring eWOM adoption on social networking sites from affective and curiosity perspectives. Internat. J. Electronic Commerce 18(3):67–102.Crossref, Google Scholar
• Farrell J, Saloner G (1986) Installed base and compatibility: Innovation, product preannouncements, and predation. Amer. Econom. Rev. 76(5):940–955.Google Scholar
• Filieri R (2015) What makes online reviews helpful? A diagnosticity-adoption framework to explain informational and normative influences in e-WOM. J. Bus. Res. 68(6):1261–1270.Crossref, Google Scholar
• Filieri R, Hofacker CF, Alguezaui S (2018) What makes information in online consumer reviews diagnostic over time? The role of review relevancy, factuality, currency, source credibility and ranking score. Comput. Human Behav. 80:122–131.Crossref, Google Scholar
• Fishbein M, Ajzen I (1975) Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research (Addison-Wesley, Reading, MA).Google Scholar
• Fragale AR, Heath C (2004) Evolving informational credentials: The (mis)attribution of believable facts to credible sources. Personality Soc. Psych. Bull. 30(2):225–236.Crossref, Google Scholar
• Ghasemaghaei M, Calic G (2019) Can big data improve firm decision quality? The role of data quality and data diagnosticity. Decision Support Systems 120:38–49.Crossref, Google Scholar
• Goodhue DL (1995) Understanding user evaluations of information systems. Management Sci. 41(12):1827–1844.Link, Google Scholar
• Goodhue DL, Thompson RL (1995) Task-technology fit and individual performance. Management Inform. Systems Quart. 19(2):213–236.Crossref, Google Scholar
• Gray PH, Parise S, Iyer B (2011) Innovation impacts of using social bookmarking systems. Management Inform. Systems Quart. 35(3):629–643.Crossref, Google Scholar
• Hair JF, Black WC, Babin BJ, Anderson RE (2009) Multivariate Data Analysis, 7th ed. (Prentice Hall, Upper Saddle River, NJ).Google Scholar
• Hayes AF (2017) Introduction to Mediation, Moderation, and Conditional Process Analysis, Second Edition: A Regression-Based Approach (Guilford Publications, New York).Google Scholar
• Hayes AF, Preacher KJ (2014) Statistical mediation analysis with a multicategorical independent variable. British J. Math. Statist. Psych. 67(3):451–470.Crossref, Google Scholar
• Herr PM, Kardes FR, Kim J (1991) Effects of word-of-mouth and product-attribute information on persuasion: An accessibility-diagnosticity perspective. J. Consumer Res. 17(4):454–462.Crossref, Google Scholar
• Hess T, Fuller M, Campbell D (2009) Designing interfaces with social presence: Using vividness and extraversion to create social recommendation agents. J. Assoc. Inform. Systems 10(12):889–919.Google Scholar
• Hinkelmann K, Kempthorne O (2008) Design and Analysis of Experiments, Introduction to Experimental Design, 2nd ed. (Wiley-Interscience, Hoboken, NJ).Google Scholar
• Hoch SJ, Deighton J (1989) Managing what consumers learn from experience. J. Marketing 53(2):1–20.Crossref, Google Scholar
• Hovland CI, Weiss W (1951) The influence of source credibility on communication effectiveness. Public Opinion Quart. 15(4):635–650.Crossref, Google Scholar
• Hu L, Bentler PM (1999) Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria vs. new alternatives. Structural Equation Model. 6(1):1–55.Crossref, Google Scholar
• Jain SP, Posavac SS (2001) Prepurchase attribute verifiability, source credibility, and persuasion. J. Consumer Psych. 11(3):169–180.Crossref, Google Scholar
• Jain SP, Buchanan B, Maheswaran D (2000) Comparative vs. noncomparative advertising: The moderating impact of prepurchase attribute verifiability. J. Consumer Psych. 9(4):201–211.Crossref, Google Scholar
• Janze C, Risius M (2017) Automatic detection of fake news on social media platforms. Proc. 21st Pacific Asia Conf. Inform. Systems (Association for Information Systems, Atlanta, GA).Google Scholar
• Jiang Z, Benbasat I (2004) Virtual product experience: Effects of visual and functional control of products on perceived diagnosticity and flow in electronic shopping. J. Management Inform. Systems 21(3):111–147.Crossref, Google Scholar
• Jiang Z, Benbasat I (2007) The effects of presentation formats and task complexity on online consumers’ product understanding. Management Inform. Systems Quart. 31(3):475–500.Crossref, Google Scholar
• Jung H (2011) Signaling quality with new product preannouncements: Vaporware and the role of reference quality. J. Bus. Res. 64(11):1251–1258.Crossref, Google Scholar
• Kahneman D (2011) Thinking, Fast and Slow (Farrar, Straus and Giroux, New York).Google Scholar
• Kamins MA, Folkes VS, Perner L (1997) Consumer responses to rumors: Good news, bad news. J. Consumer Psych. 6(2):165–187.Crossref, Google Scholar
• Kankanhalli A, Tan BCY, Wei KK (2005) Contributing knowledge to electronic knowledge repositories: An empirical investigation. Management Inform. Systems Quart. 29(1):113–143.Crossref, Google Scholar
• Karahanna E, Xin Xu S, Xu Y, Zhang NA (2018) The needs–affordances–features perspective for the use of social media. Management Inform. Systems Quart. 42(3):737–756.Crossref, Google Scholar
• Kejriwal M, Wang Q, Li H, Wang L (2021) An empirical study of emoji usage on Twitter in linguistic and national contexts. Online Soc. Networks Media 24:1–23.Crossref, Google Scholar
• Kempf DS, Smith RE (1998) Consumer processing of product trial and the influence of prior advertising: A structural modeling approach. J. Marketing Res. 35(3):325–338.Crossref, Google Scholar
• Kisielius J, Sternthal B (1984) Detecting and explaining vividness effects in attitudinal judgments. J. Marketing Res. 21(1):54–64.Crossref, Google Scholar
• Kuan K, Hui KL, Prasarnphanich P, Lai HY (2015) What makes a review voted? An empirical investigation of review voting in online review systems. J. Assoc. Inform. Systems 16(1):48–71.Google Scholar
• Kwak H, Lee C, Park H, Moon S (2010) What is Twitter, a social network or a news media? Proc. 19th Internat. Conf. World Wide Web (Association for Computing Machinery, New York), 591–600.Google Scholar
• Lee TB (2017) Apple’s anti-leaking strategy just leaked. Vox.com (June 20), https://www.vox.com/new-money/2017/6/20/15838284/apple-leak-leak.Google Scholar
• Lee K, Caverlee J, Webb S (2010) Uncovering social spammers: social honeypots + machine learning. Proc. 33rd Internat. ACM SIGIR Conf. Res. Development Inform. Retrieval (Association for Computing Machinery, New York), 435–442.Google Scholar
• Lee RP, Chen Q, Hartmann NN (2016) Enhancing stock market return with new product preannouncements: The role of information quality and innovativeness. J. Product Innovation Management 33(4):455–471.Crossref, Google Scholar
• Lee YW, Strong DM, Kahn BK, Wang RY (2002) AIMQ: A methodology for information quality assessment. Inform. Management 40(2):133–146.Crossref, Google Scholar
• Lindell MK, Whitney DJ (2001) Accounting for common method variance in cross-selectional research designs. J. Appl. Psych. 86(1):114–121.Crossref, Google Scholar
• MacCallum RC, Browne MW, Sugawara HM (1996) Power analysis and determination of sample size for covariance structure modeling. Psych. Methods 1(2):130–149.Crossref, Google Scholar
• Malhotra NK, Kim SS, Patil A (2006) Common method variance in is research: A comparison of alternative approaches and a reanalysis of past research. Management Sci. 52(12):1865–1883.Link, Google Scholar
• Mazzoni GAL, Loftus EF, Kirsch I (2001) Changing beliefs about implausible autobiographical events: A little plausibility goes a long way. J. Experiment. Psych. Appl. 7(1):51–59.Crossref, Google Scholar
• McHugh ML (2012) Interrater reliability: The kappa statistic. Biochemia Medica 22(3):276–282.Crossref, Google Scholar
• Miller DE (2005) Rumor: An examination of some stereotypes. Symbolic Interaction 28(4):505–519.Crossref, Google Scholar
• Morley DD, Walker KB (1987) The role of importance, novelty, and plausibility in producing belief change. Comm. Monographs 54(4):436–442.Crossref, Google Scholar
• Mudambi SM, Schuff D (2010) Research note: What makes a helpful online review? A study of customer reviews on Amazon.com. Management Inform. Systems Quart. 34(1):185–200.Crossref, Google Scholar
• Nahari G, Vrij A, Fisher RP (2014) The verifiability approach: Countermeasures facilitate its ability to discriminate between truths and lies. Appl. Cognitive Psych. 28(1):122–128.Crossref, Google Scholar
• Navis C, Glynn MA (2011) Legitimate distinctiveness and the entrepreneurial identity: Influence on investor judgments of new venture plausibility. Acad. Management Rev. 36(3):479–499.Crossref, Google Scholar
• Needleman SE (2021) What is Parler? Conservative social-media app denied Apple’s App Store access. Wall Street J. (March 11), https://www.wsj.com/articles/what-is-parler-app-apple-android-11610478890.Google Scholar
• Newman ML, Pennebaker JW, Berry DS, Richards JM (2003) Lying words: Predicting deception from linguistic styles. Personality Soc. Psych. Bull. 29(5):665–675.Crossref, Google Scholar
• Nicolaou AI, McKnight DH (2006) Perceived information quality in data exchanges: Effects on risk, trust, and intention to use. Inform. Systems Res. 17(4):332–351.Link, Google Scholar
• Nicolaou AI, Ibrahim M, van Heck E (2013) Information quality, trust, and risk perceptions in electronic data exchanges. Decision Support Systems 54(2):986–996.Crossref, Google Scholar
• Nisbett RE, Ross L (1980) Human Inference: Strategies and Shortcomings of Social Judgment (Prentice-Hall, Englewood Cliffs, NJ).Google Scholar
• Oh O, Agrawal M, Rao HR (2013) Community intelligence and social media services: A rumor theoretic analysis of tweets during social crises. Management Inform. Systems Quart. 37(2):407–426.Crossref, Google Scholar
• Pavlou PA, Liang H, Xue Y (2007) Understanding and mitigating uncertainty in online exchange relationships: A principal-agent perspective. Management Inform. Systems Quart. 31(1):105–136.Crossref, Google Scholar
• Pennebaker JW, Chung CK, Ireland M, Gonzales A, Booth RJ (2007) The development and psychometric properties of LIWC2007. White paper, LIWC.net, Austin, TX.Google Scholar
• Pennebaker JW, Chung CK, Frazee J, Lavergne GM, Beaver DI (2014) When small words foretell academic success: The case of college admissions essays. PLoS One 9(12):e115844.Crossref, Google Scholar
• Petter S, DeLone W, McLean ER (2013) Information systems success: The quest for the independent variables. J. Management Inform. Systems 29(4):7–62.Crossref, Google Scholar
• Petty RE, Cacioppo JT (1986) The elaboration likelihood model of persuasion. Petty RE, Cacioppo JT, eds. Communication and Persuasion: Central and Peripheral Routes to Attitude Change (Springer, New York), 1–24.Google Scholar
• Pornpitakpan C (2004) The persuasiveness of source credibility: A critical review of five decades’ evidence. J. Appl. Soc. Psych. 34(2):243–281.Crossref, Google Scholar
• Roscoe JT (1975) Fundamental Research Statistics for the Behavioral Sciences (Holt, Rinehart and Winston, New York).Google Scholar
• Rosenthal PI (1971) Specificity, verifiability, and message credibility. Quart. J. Speech 57(4):393–401.Crossref, Google Scholar
• Rosnow RL (1980) Psychology of rumor reconsidered. Psych. Bull. 87(3):578–591.Crossref, Google Scholar
• Rosnow RL (1991) Inside rumor: A personal journey. Amer. Psychologist 46(5):484–496.Crossref, Google Scholar
• Rosseel Y (2012) lavaan: An R package for structural equation modeling. J. Statist. Software 48(2):1–36.Crossref, Google Scholar
• Saul H (2014) McDonald’s answers pink slime and worm meat rumours by inviting cameras into a burger factory. Independent (October 16), https://www.independent.co.uk/life-style/food-and-drink/mcdonald-s-answers-pink-slime-and-worm-meat-rumours-inviting-cameras-burger-factory-9793468.html.Google Scholar
• Sekaran U, Bougie R (2016) Research Methods for Business: A Skill Building Approach (John Wiley & Sons, Chichester, West Sussex, England).Google Scholar
• Shi Z, Rui H, Whinston AB (2014) Content sharing in a social broadcasting environment: Evidence from Twitter. Management Inform. Systems Quart. 38(1):123–142.Crossref, Google Scholar
• Shibutani T (1966) Improvised News: A Sociological Study of Rumor (Bobbs-Merrill, Indianapolis, IN).Google Scholar
• Steuer J (1992) Defining virtual reality: Dimensions determining telepresence. J. Comm. 42(4):73–93.Crossref, Google Scholar
• Stevens LE, Fiske ST (1995) Motivation and cognition in social life: A social survival perspective. Soc. Cognition 13(3):189–214.Crossref, Google Scholar
• Sundar SS, Kalyanaraman S (2004) Arousal, memory, and impression-formation effects of animation speed in web advertising. J. Advertising 33(1):7–17.Crossref, Google Scholar
• Szpunar KK, Schacter DL (2013) Get real: Effects of repeated simulation and emotion on the perceived plausibility of future experiences. J. Experiment Psych. General 142(2):323–327.Crossref, Google Scholar
• Thatcher JB, Zimmer JC, Gundlach MJ, McKnight DH (2008) Internal and external dimensions of computer self-efficacy: An empirical examination. IEEE Trans. Engrg. Management 55(4):628–644.Crossref, Google Scholar
• Todd RM, Talmi D, Schmitz TW, Susskind J, Anderson AK (2012) Psychophysical and neural evidence for emotion-enhanced perceptual vividness. J. Neurosci. 32(33):11201–11212.Crossref, Google Scholar
• Torres R, Gerhart N, Negahban A (2018) Epistemology in the era of fake news: An exploration of information verification behaviors among social networking site users. SIGMIS Database 49(3):78–97.Crossref, Google Scholar
• Tversky A, Kahneman D (1973) Availability: A heuristic for judging frequency and probability. Cognitive Psych. 5(2):207–232.Crossref, Google Scholar
• Tversky A, Kahneman D (1974) Judgment under uncertainty: Heuristics and biases. Science 185(4157):1124–1131.Crossref, Google Scholar
• Tybout AM, Calder BJ, Sternthal B (1981) Using information processing theory to design marketing strategies. J. Marketing Res. 18(1):73–79.Crossref, Google Scholar
• Unger LS, Kernan JB (1983) On the meaning of leisure: An investigation of some determinants of the subjective experience. J. Consumer Res. 9(4):381–392.Crossref, Google Scholar
• Venkatesh V, Brown SA, Bala H (2013) Bridging the qualitative-quantitative divide: Guidelines for conducting mixed methods research in information systems. Management Inform. Systems Quart. 37(1):21–54.Crossref, Google Scholar
• Venkatesh V, Brown S, Sullivan Y (2016) Guidelines for conducting mixed-methods research: An extension and illustration. J. Assoc. Inform. Systems 17(7):435–495.Google Scholar
• Venkatesh V, Brown SA, Maruping LM, Bala H (2008) Predicting different conceptualizations of system USE: The competing roles of behavioral intention, facilitating conditions, and behavioral expectation. Management Inform. Systems Quart. 32(3):483–502.Crossref, Google Scholar
• Viera AJ, Garrett JM (2005) Understanding interobserver agreement: The kappa statistic. Family Medicine 37(5):360–363.Google Scholar
• Vosoughi S, Roy D, Aral S (2018) The spread of true and false news online. Science 359(6380):1146–1151.Crossref, Google Scholar
• Vrij A, Deeb H, Leal S, Granhag PA, Fisher RP (2021) Plausibility: A verbal cue to veracity worth examining? Eur. J. Psych. Appl. Legal Context 13(2):47–53.Google Scholar
• Wang RY, Strong DM (1996) Beyond accuracy: What data quality means to data consumers. J. Management Inform. Systems 12(4):5–33.Crossref, Google Scholar
• Wasko MM, Faraj S (2000) “It is what one does”: Why people participate and help others in electronic communities of practice. J. Strategic Inform. Systems 9(2):155–173.Crossref, Google Scholar
• Wasko MM, Faraj S (2005) Why should I share? Examining social capital and knowledge contribution in electronic networks of practice. Management Inform. Systems Quart. 29(1):35–57.Crossref, Google Scholar
• Watson A (2020) Level of trust in news sources in North America 2018. Statista (April 18), https://www.statista.com/statistics/620290/news-sources-trustworthiness/.Google Scholar
• Watts S, Zhang W (2008) Capitalizing on content: Information adoption in two online communities. J. Assoc. Inform. Systems 9(2):73–94.Google Scholar
• Weick KE, Sutcliffe KM, Obstfeld D (2005) Organizing and the process of sensemaking. Organ. Sci. 16(4):409–421.Link, Google Scholar
• Wells JD, Campbell DE, Valacich JS, Featherman M (2010) The effect of perceived novelty on the adoption of information technology innovations: A risk/reward perspective. Decision Sci. 41(4):813–843.Crossref, Google Scholar
• White RE, Kuehn MM, Duckworth AL, Kross E, Ayduk Ö (2019) Focusing on the future from afar: Self-distancing from future stressors facilitates adaptive coping. Emotion 19(5):903–916.Crossref, Google Scholar
• Xia M, Huang Y, Duan W, Whinston AB (2011) Research note—To continue sharing or not to continue sharing? An empirical analysis of user decision in peer-to-peer sharing networks. Inform. Systems Res. 23(1):247–259.Link, Google Scholar
• Yang C, Harkreader R, Gu G (2013) Empirical evaluation and new design for fighting evolving Twitter spammers. IEEE Trans. Inform. Forensics Security 8(8):1280–1293.Crossref, Google Scholar
• Yi C, Jiang Z, Benbasat I (2017) Designing for diagnosticity and serendipity: An investigation of social product-search mechanisms. Inform. Systems Res. 28(2):413–429.Link, Google Scholar
• Yoo E, Rand W, Eftekhar M, Rabinovich E (2016) Evaluating information diffusion speed and its determinants in social media networks during humanitarian crises. J. Oper. Management 45:123–133.Crossref, Google Scholar