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在线调查中自我报告的分享政治新闻文章的意愿与在 Twitter 上的实际分享相关。

Self-reported willingness to share political news articles in online surveys correlates with actual sharing on Twitter.

机构信息

Sloan School of Managment, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.

Hill/Levene Schools of Business, University of Regina, Regina, Saskatchewan, Canada.

出版信息

PLoS One. 2020 Feb 10;15(2):e0228882. doi: 10.1371/journal.pone.0228882. eCollection 2020.

Abstract

There is an increasing imperative for psychologists and other behavioral scientists to understand how people behave on social media. However, it is often very difficult to execute experimental research on actual social media platforms, or to link survey responses to online behavior in order to perform correlational analyses. Thus, there is a natural desire to use self-reported behavioral intentions in standard survey studies to gain insight into online behavior. But are such hypothetical responses hopelessly disconnected from actual sharing decisions? Or are online survey samples via sources such as Amazon Mechanical Turk (MTurk) so different from the average social media user that the survey responses of one group give little insight into the on-platform behavior of the other? Here we investigate these issues by examining 67 pieces of political news content. We evaluate whether there is a meaningful relationship between (i) the level of sharing (tweets and retweets) of a given piece of content on Twitter, and (ii) the extent to which individuals (total N = 993) in online surveys on MTurk reported being willing to share that same piece of content. We found that the same news headlines that were more likely to be hypothetically shared on MTurk were also shared more frequently by Twitter users, r = .44. For example, across the observed range of MTurk sharing fractions, a 20 percentage point increase in the fraction of MTurk participants who reported being willing to share a news headline on social media was associated with 10x as many actual shares on Twitter. We also found that the correlation between sharing and various features of the headline was similar using both MTurk and Twitter data. These findings suggest that self-reported sharing intentions collected in online surveys are likely to provide some meaningful insight into what content would actually be shared on social media.

摘要

心理学家和其他行为科学家越来越需要了解人们在社交媒体上的行为方式。然而,在实际的社交媒体平台上执行实验研究,或者将调查回复与在线行为联系起来以进行相关分析,通常是非常困难的。因此,人们自然希望在标准调查研究中使用自我报告的行为意图来深入了解在线行为。但是,这些假设性的回复是否与实际的分享决策完全脱节?或者通过亚马逊 Mechanical Turk (MTurk) 等来源进行的在线调查样本与普通社交媒体用户如此不同,以至于一组的调查回复对另一组的平台行为几乎没有洞察力?在这里,我们通过检查 67 条政治新闻内容来研究这些问题。我们评估了以下两个方面之间是否存在有意义的关系:(i) 给定内容在 Twitter 上的分享(推文和转发)水平,以及 (ii) 在 MTurk 上进行的在线调查中个人(总 N = 993)报告愿意分享同一内容的程度。我们发现,在 MTurk 上更有可能被假设分享的相同新闻标题,也被 Twitter 用户更频繁地分享,r =.44。例如,在观察到的 MTurk 分享分数范围内,MTurk 参与者中愿意在社交媒体上分享新闻标题的比例增加 20 个百分点,与 Twitter 上的实际分享次数增加 10 倍相关。我们还发现,使用 MTurk 和 Twitter 数据,分享与标题各种特征之间的相关性相似。这些发现表明,在在线调查中收集的自我报告的分享意图可能会为实际在社交媒体上分享的内容提供一些有意义的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92f9/7010247/14ce8de3c079/pone.0228882.g001.jpg

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