Empirical evidence that there is social influence on private wine evaluations that is greater than the effect of experts’ ratings & prices combined; this influence comes mainly from the first few group members, & increases as a function of source uniformity

Omer Gokcekus, Miles Hewstone, and Huseyin Cakal (2018) In Vino Veritas? Social Influence on “Private” Wine Evaluations at a Wine Social Networking Site. Handbook of the Economics of Wine: pp. 423-437. https://doi.org/10.1142/9789813232754_0018

Abstract: An archival analysis of evaluations of wines provides a unique context in which to investigate social influence in a naturalistic setting. We conducted analyzes based on 6,157 notes about 106 wines posted by wine drinkers at a wine social networking site. Our findings suggest that social influence on private wine evaluations occurred by communicating a descriptive norm via written information. We provide empirical evidence that there is social influence on private wine evaluations that is greater than the effect of experts’ ratings and prices combined. This influence comes mainly from the first few group members, and increases as a function of source uniformity. Together with a lack of evidence that more credible or expert members have more influence, these findings suggest that influence in this setting is normative rather than informational. Results have implications for widespread effects of social influence on consumer and other websites where we are subject to the power of others’ opinions.

Probability of sharing political fake news online is higher in males than females & and older people more than youngers; democrat voters have less probability to share political fake news than independent voters (there is no statistical significance between democrats and republicans)

The Sociology of Fake News: Factors Affecting the Probability of Sharing Political Fake News Online. Manuel Goyanes, Ana Lavin. Media@LSE Working Paper #55, 2018, https://www.researchgate.net/publication/325721782

Abstract: Drawing on recent literature on fake news, this working paper sheds light on the demographic factors and situational predictors that influence the probability to share political fake news through social media platforms. By using a representative sample of 1.002 US adults from the Pew Research Center, the results of the logistic regression analysis revealed relationships between the probability to share political fake news online and predictor variables such as demographics (age, gender, political orientation and income), and situational factors (perception of frequency of political fake news online, previous unconsciously fake news sharing and perception of responsibility [of different agents]). The research offers evidence regarding the prototype user that contributes to the spread of misinformation and the main implications that this phenomenon entails for professional journalism.

---
By using a logistic regression analysis, nine main findings emerged: (1) the probability of sharing political fake news online is higher in males than females; (2) older people are more likely to share political fake news online than younger people; (3) people with lower incomes have more probability to share political fake news online; (4) democrat voters have less probability to share political fake news than independent voters (there is no statistical significance between democrats and republicans); (5) people who have a high perception of frequency of online fake news are more likely to share political fake news; (6) people who inadvertently have shared fake news have less probability to share political fake news online on purpose; (7) people who grant great responsibility to the public in preventing fake news stories from gaining attention are less likely to share political fake news; (8) people who grant great responsibility to social networking sites in preventing fake news stories from gaining attention are more likely to share political fake news stories and (9) democrat‐female voters are less likely to share political fake news than male‐independent voters.


Check also Lazy, not biased: Susceptibility to partisan fake news is better explained by lack of reasoning than by motivated reasoning. Gordon Pennycook, David G. Rand. Cognition, https://www.bipartisanalliance.com/2018/06/susceptibility-to-partisan-fake-news-is.html

Susceptibility to partisan fake news is better explained by lack of reasoning (lazyness in thinking) than by motivated reasoning (partisanship)

Also Read All About It: The Politicization of “Fake News” on Twitter. John Brummette et al. Journalism & Mass Communication Quarterly, Volume: 95 issue: 2, page(s): 497-517. https://www.bipartisanalliance.com/2018/06/fake-news-is-politicized-term-where.html

“Fake news” is a politicized term where conversations overshadowed logical & important discussions of the term; social media users from opposing political parties communicate in homophilous environments & use “fake news” to disparage the opposition & condemn real information

And: Fake news and post-truth pronouncements in general and in early human development. Victor Grech. Early Human Development, http://www.bipartisanalliance.com/2017/09/fake-news-and-post-truth-pronouncements.html

And: Consumption of fake news is a consequence, not a cause of their readers’ voting preferences. Kahan, Dan M., Misinformation and Identity-Protective Cognition (October 2, 2017). Social Science Research Network, http://www.bipartisanalliance.com/2017/10/consumption-of-fake-news-is-consequence.html

And: Barbera, Pablo and Tucker, Joshua A. and Guess, Andrew and Vaccari, Cristian and Siegel, Alexandra and Sanovich, Sergey and Stukal, Denis and Nyhan, Brendan (2018) Social media, political polarization, and political disinformation: a review of the scientific literature. William + Flora Hewlett Foundation, California. https://www.bipartisanalliance.com/2018/04/a-great-deal-of-public-outcry-against.html

"A great deal of the public outcry against fake news, echo chambers and polarization on social media is itself based on misinformation"

Women expressed higher educational preferences during their years of maximum fertility, their demand choosiness decreased with age; men’s choosiness remained stable until the 40s, from which it increased until their peak years of career-earnings potential

Do Men and Women Know What They Want? Sex Differences in Online Daters’ Educational Preferences. Stephen Whyte et al. Psychological Science, https://doi.org/10.1177/0956797618771081

Abstract: Using a unique cross-sectional data set of dating website members’ educational preferences for potential mates (N = 41,936), we showed that women were more likely than men to stipulate educational preferences at all ages. When members indifferent to educational level were excluded, however, the specificity of men’s and women’s preferences did differ for different age groups. That is, whereas women expressed more refined educational preferences during their years of maximum fertility, their demand specificity decreased with age. Men’s specificity, in contrast, remained stable until the 40s, when it was greater than that of postreproductive women, and then was higher during their peak years of career-earnings potential. Further, when individuals’ level of education was controlled for, women (compared with men) were more likely to state a higher minimum preference for educational level in a potential mate.

Keywords: parental-investment theory, educational preference, sex differences, online dating, mate choice