scholarly journals Shared Partisanship Dramatically Increases Social Tie Formation in a Twitter Field Experiment

2020 ◽  
Author(s):  
Mohsen Mosleh ◽  
Cameron Martel ◽  
Dean Eckles ◽  
David Gertler Rand

Americans are much more likely to be socially connected to co-partisans, both in daily life and on social media. But this observation does not necessarily mean that shared partisanship per se drives social tie formation, because partisanship is confounded with many other factors. Here, we test the causal effect of shared partisanship on the formation of social ties in a field experiment on Twitter. We created bot accounts that self-identified as people who favored the Democratic or Republican party, and that varied in the strength of that identification. We then randomly assigned 842 Twitter users to be followed by one of our accounts. Users were roughly three times more likely to reciprocally follow-back bots whose partisanship matched their own, and this was true regardless of the bot’s strength of identification. Interestingly, there was no partisan asymmetry in this preferential follow-back behavior: Democrats and Republicans alike were much more likely to reciprocate follows from co-partisans. These results demonstrate a strong causal effect of shared partisanship on the formation of social ties in an ecologically valid field setting, and have important implications for political psychology, social media, and the politically polarized state of the American public.

2021 ◽  
Vol 118 (7) ◽  
pp. e2022761118 ◽  
Author(s):  
Mohsen Mosleh ◽  
Cameron Martel ◽  
Dean Eckles ◽  
David G. Rand

Americans are much more likely to be socially connected to copartisans, both in daily life and on social media. However, this observation does not necessarily mean that shared partisanship per se drives social tie formation, because partisanship is confounded with many other factors. Here, we test the causal effect of shared partisanship on the formation of social ties in a field experiment on Twitter. We created bot accounts that self-identified as people who favored the Democratic or Republican party and that varied in the strength of that identification. We then randomly assigned 842 Twitter users to be followed by one of our accounts. Users were roughly three times more likely to reciprocally follow-back bots whose partisanship matched their own, and this was true regardless of the bot’s strength of identification. Interestingly, there was no partisan asymmetry in this preferential follow-back behavior: Democrats and Republicans alike were much more likely to reciprocate follows from copartisans. These results demonstrate a strong causal effect of shared partisanship on the formation of social ties in an ecologically valid field setting and have important implications for political psychology, social media, and the politically polarized state of the American public.


2022 ◽  
Author(s):  
Qi Yang ◽  
Mohsen Mosleh ◽  
David Gertler Rand ◽  
Tauhid Zaman

Many social media users try to obtain as many followers as possible in a social network to gain influence, a challenge that is often referred to as the follow back problem. In this work we study different strategies for this problem in the context of politically polarized social networks and study how political partisanship affect social media users' propensity to follow each other. We test how contact strategy (liking, following) interacts with partisan alignment when trying to induce users to follow back. To do so, we conduct a field experiment on Twitter where we target N=8,104 active users using bot accounts that present as human. We found that users were more than twice as likely to reciprocally follow back bots whose partisanship matched their own. Conversely, when the only form of contact between the bot and the user was the bot liking the user’s posts, the follow rate was extremely low regardless of partisan alignment – and liking a user’s content and following them led to no increase in follow-back relative to just following the user. Finally, we found no partisanship asymmetries, such that Democrats and Republicans preferentially followed co-partisans to the same extent. Our results demonstrate the important impact of following users and having shared partisanship – and the irrelevance of liking users’ content – on solving the follow back problem.


2018 ◽  
Author(s):  
Andrea Pereira ◽  
Jay Joseph Van Bavel ◽  
Elizabeth Ann Harris

Political misinformation, often called “fake news”, represents a threat to our democracies because it impedes citizens from being appropriately informed. Evidence suggests that fake news spreads more rapidly than real news—especially when it contains political content. The present article tests three competing theoretical accounts that have been proposed to explain the rise and spread of political (fake) news: (1) the ideology hypothesis— people prefer news that bolsters their values and worldviews; (2) the confirmation bias hypothesis—people prefer news that fits their pre-existing stereotypical knowledge; and (3) the political identity hypothesis—people prefer news that allows their political in-group to fulfill certain social goals. We conducted three experiments in which American participants read news that concerned behaviors perpetrated by their political in-group or out-group and measured the extent to which they believed the news (Exp. 1, Exp. 2, Exp. 3), and were willing to share the news on social media (Exp. 2 and 3). Results revealed that Democrats and Republicans were both more likely to believe news about the value-upholding behavior of their in-group or the value-undermining behavior of their out-group, supporting a political identity hypothesis. However, although belief was positively correlated with willingness to share on social media in all conditions, we also found that Republicans were more likely to believe and want to share apolitical fake new. We discuss the implications for theoretical explanations of political beliefs and application of these concepts in in polarized political system.


2020 ◽  
Author(s):  
Aleksandra Urman ◽  
Stefania Ionescu ◽  
David Garcia ◽  
Anikó Hannák

BACKGROUND Since the beginning of the COVID-19 pandemic, scientists have been willing to share their results quickly to speed up the development of potential treatments and/or a vaccine. At the same time, traditional peer-review-based publication systems are not always able to process new research promptly. This has contributed to a surge in the number of medical preprints published since January 2020. In the absence of a vaccine, preventative measures such as social distancing are most helpful in slowing the spread of COVID-19. Their effectiveness can be undermined if the public does not comply with them. Hence, public discourse can have a direct effect on the progression of the pandemic. Research shows that social media discussions on COVID-19 are driven mainly by the findings from preprints, not peer-reviewed papers, highlighting the need to examine the ways medical preprints are shared and discussed online. OBJECTIVE We examine the patterns of medRxiv preprint sharing on Twitter to establish (1) whether the number of tweets linking to medRxiv increased with the advent of the COVID-19 pandemic; (2) which medical preprints were mentioned on Twitter most often; (3) whether medRxiv sharing patterns on Twitter exhibit political partisanship; (4) whether the discourse surrounding medical preprints among Twitter users has changed throughout the pandemic. METHODS The analysis is based on tweets (n=557,405) containing links to medRxriv preprint repository that were posted between the creation of the repository in June 2019 and June 2020. The study relies on a combination of statistical techniques and text analysis methods. RESULTS Since January 2020, the number of tweets linking to medRxiv has increased drastically, peaking in April 2020 with a subsequent cool-down. Before the pandemic, preprints were shared predominantly by users we identify as medical professionals and scientists. After January 2020, other users, including politically-engaged ones, have started increasingly tweeting about medRxiv. Our findings indicate a political divide in sharing patterns of the top-10 most-tweeted preprints. All of them were shared more frequently by users who describe themselves as Republicans than by users who describe themselves as Democrats. Finally, we observe a change in the discourse around medRxiv preprints. Pre-pandemic tweets linking to them were predominantly using the word “preprint”. In February 2020 “preprint” was taken over by the word “study”. Our analysis suggests this change is at least partially driven by politically-engaged users. Widely shared medical preprints can have a direct effect on the public discourse around COVID-19, which in turn can affect the societies’ willingness to comply with preventative measures. This calls for an increased responsibility when dealing with medical preprints from all parties involved: scientists, preprint repositories, media, politicians, and social media companies. CONCLUSIONS Widely shared medical preprints can have a direct effect on the public discourse around COVID-19, which in turn can affect the societies’ willingness to comply with preventative measures. This calls for an increased responsibility when dealing with medical preprints from all parties involved: scientists, preprint repositories, media, politicians, and social media companies.


2020 ◽  
Author(s):  
Ethan Kaji ◽  
Maggie Bushman

BACKGROUND Adolescents with depression often turn to social media to express their feelings, for support, and for educational purposes. Little is known about how Reddit, a forum-based platform, compares to Twitter, a newsfeed platform, when it comes to content surrounding depression. OBJECTIVE The purpose of this study is to identify differences between Reddit and Twitter concerning how depression is discussed and represented online. METHODS A content analysis of Reddit posts and Twitter posts, using r/depression and #depression, identified signs of depression using the DSM-IV criteria. Other youth-related topics, including School, Family, and Social Activity, and the presence of medical or promotional content were also coded for. Relative frequency of each code was then compared between platforms as well as the average DSM-IV score for each platform. RESULTS A total of 102 posts were included in this study, with 53 Reddit posts and 49 Twitter posts. Findings suggest that Reddit has more content with signs of depression with 92% than Twitter with 24%. 28.3% of Reddit posts included medical content compared to Twitter with 18.4%. 53.1% of Twitter posts had promotional content while Reddit posts didn’t contain promotional content. CONCLUSIONS Users with depression seem more willing to discuss their mental health on the subreddit r/depression than on Twitter. Twitter users also use #depression with a wider variety of topics, not all of which actually involve a case of depression.


2021 ◽  
pp. 004728162110078
Author(s):  
Shanna Cameron ◽  
Alexandra Russell ◽  
Luke Brake ◽  
Katherine Fredlund ◽  
Angela Morris

This article engages with recent discussions in the field of technical communication that call for climate change research that moves beyond the believer/denier dichotomy. For this study, our research team coded 900 tweets about climate change and global warming for different emotions in order to understand how Twitter users rely on affect rhetorically. Our findings use quantitative content analysis to challenge current assumptions about writing and affect on social media, and our results indicate a number of arenas for future research on affect, global warming, and rhetoric.


Author(s):  
Giandomenico Di Domenico ◽  
Annamaria Tuan ◽  
Marco Visentin

AbstractIn the wake of the COVID-19 pandemic, unprecedent amounts of fake news and hoax spread on social media. In particular, conspiracy theories argued on the effect of specific new technologies like 5G and misinformation tarnished the reputation of brands like Huawei. Language plays a crucial role in understanding the motivational determinants of social media users in sharing misinformation, as people extract meaning from information based on their discursive resources and their skillset. In this paper, we analyze textual and non-textual cues from a panel of 4923 tweets containing the hashtags #5G and #Huawei during the first week of May 2020, when several countries were still adopting lockdown measures, to determine whether or not a tweet is retweeted and, if so, how much it is retweeted. Overall, through traditional logistic regression and machine learning, we found different effects of the textual and non-textual cues on the retweeting of a tweet and on its ability to accumulate retweets. In particular, the presence of misinformation plays an interesting role in spreading the tweet on the network. More importantly, the relative influence of the cues suggests that Twitter users actually read a tweet but not necessarily they understand or critically evaluate it before deciding to share it on the social media platform.


2021 ◽  
pp. 1-16
Author(s):  
Sarah Hendrica Bickerton ◽  
Karl Löfgren

Public engagement is a gendered experience, whether offline or online, something which is reflected in women’s experiences of social media. In this article, we seek to systematically explore the experiences from politically engaged women twitter users in New Zealand in order to draw some lessons, through a thematic and interpretative analytical approach, at four different strategic levels on how to deflect intimidating and aggressive behaviour. We conclude that understanding strategically how structural social locations like gender effect the ability to contribute to political participation and engagement, if addressed, can produce more inclusive and productive online political and policy spaces. Further, this strategic approach involves connecting together different levels of response to online negativity such as platform tools, space-curation, and monitoring, having these made coherent with each other, as well as with this strategic understanding of how structural social location plays into access and use of online political and policy spaces.


2021 ◽  
Author(s):  
Valentin Ritschl ◽  
Fabian Eibensteiner ◽  
Erika Mosor ◽  
Maisa Omara ◽  
Lisa Sperl ◽  
...  

BACKGROUND On January 30, 2020, the World Health Organization (WHO) Emergency Committee declared the rapid worldwide spread of Coronavirus Disease 2019 (COVID-19) a global health emergency. By December 2020, the safety and efficacy of the first COVID-19 vaccines had been demonstrated. However, global vaccination coverage rates have remained below expectations. Mandatory vaccination is now being controversially discussed and has been enacted in some developed countries, while the vaccination rate is very low in many developing countries. We used the Twitter survey system as a viable method to quickly and comprehensively gather international public health insights on mandatory vaccination against COVID-19. OBJECTIVE The purpose of this study was to understand better the public's perception of mandatory COVID-19 vaccination in real-time utilizing Twitter polls. METHODS Two Twitter polls were developed to seek the public's opinion on the possibility of mandatory vaccination. The polls were pinned to the Digital Health and Patient Safety Platform's Twitter timeline for one week in mid-November 2021, three days after the official public announcement of mandatory COVID-19 vaccination in Austria. Twitter users were asked to participate and retweet the polls to reach the largest possible audience. RESULTS Our Twitter polls revealed two extremes on the topic of mandatory vaccination against COVID-19. Almost half of the respondents (49% [1,246/2,545]) favour mandatory vaccination, at least in certain areas. This attitude is in contrast to the 45.7% (1,162/2,545) who categorically reject mandatory vaccination. 26.3% (621/2,365) of participating Twitter users said they would never get vaccinated, which is reflected by the current vaccination coverage rate. Concatenating interpretation of these two polls needs to be done cautiously as participating populations might greatly differ. CONCLUSIONS Mandatory vaccination against COVID-19 (in at least certain areas) is favoured by less than 50%, whereas it is vehemently opposed by almost half of the surveyed Twitter users. Since (social) media strongly influences public perceptions and views through and social media discussions and surveys specifically susceptible to the "echo chamber effect", the results can be seen as a momentary snapshot. Therefore, the results of this study need to be complemented by long-term surveys to maintain their validity.


2021 ◽  
Author(s):  
Arash Maghsoudi ◽  
Sara Nowakowski ◽  
Ritwick Agrawal ◽  
Amir Sharafkhaneh ◽  
Sadaf Aram ◽  
...  

BACKGROUND The COVID-19 pandemic has imposed additional stress on population health that may result in a higher incidence of insomnia. In this study, we hypothesized that using natural language processing (NLP) to explore social media would help to identify the mental health condition of the population experiencing insomnia after the outbreak of COVID-19. OBJECTIVE In this study, we hypothesized that using natural language processing (NLP) to explore social media would help to identify the mental health condition of the population experiencing insomnia after the outbreak of COVID-19. METHODS We designed a pre-post retrospective study using public social media content from Twitter. We categorized tweets based on time into two intervals: prepandemic (01/01/2019 to 01/01/2020) and pandemic (01/01/2020 to 01/01/2021). We used NLP to analyze polarity (positive/negative) and intensity of emotions and also users’ tweets psychological states in terms of sadness, anxiety and anger by counting the words related to these categories in each tweet. Additionally, we performed temporal analysis to examine the effect of time on the users’ insomnia experience. RESULTS We extracted 268,803 tweets containing the word insomnia (prepandemic, 123,293 and pandemic, 145,510). The odds of negative tweets (OR, 1.31; 95% CI, 1.29-1.33), anger (OR, 1.19; 95% CI, 1.16-1.21), and anxiety (OR, 1.24; 95% CI: 1.21-1.26) were higher during the pandemic compared to prepandemic. The likelihood of negative tweets after midnight was higher than for other daily intevals, comprising approximately 60% of all negative insomnia-related tweets in 2020 and 2021 collectively. CONCLUSIONS Twitter users shared more negative tweets about insomnia during the pandemic than during the year before. Also, more anger and anxiety-related content were disseminated during the pandemic on the social media platform. Future studies using an NLP framework could assess tweets about other psychological distress, habit changes, weight gain due to inactivity, and the effect of viral infection on sleep.


Sign in / Sign up

Export Citation Format

Share Document