Yotam Shmargad
Biographic Data
| ID | 231833 |
|---|---|
| NAME | Yotam Shmargad |
| GIVEN NAMES | Yotam |
| FAMILY NAME | Shmargad |
| SIGNATURE | SHMARGAD Y |
| AFFILIATIONS | University of Arizona |
| ORCID | 0000-0001-8558-3345 |
| VERIFIED | Yes |
| TOTAL WORKS | 13 |
| TOTAL CITATIONS | 63 |
| WORKS AS AUTHOR | 13 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2017 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 4 |
Incivility in Online Discussion as a Collective Phenomenon
Drawing from dynamic systems theory, we examine how incivility is collectively constructed in an online discussion community. Using secondary data consisting of comments shared over a 3-week period to an online news community, we identified three sequences that reflect collective incivility practices. Whereas the persistent incivility sequence included a large proportion of uncivil comments, incivility occurred infrequently in the sporadic incivi…
Examining the Dynamics of Uncivil Discourse Between Sub-National Political Officials and the Public on Twitter
Despite agreement about the challenges posed by incivility for democratic discourse, much remains to be learned about how incivility manifests in interactions between the public and political elites. We examine the connections between top-down and bottom-up incivility among 22 local and state elected officials and the public over an 18-month period on Twitter. Our analyses show that incivility in a tweet from an elected official significantly inc…
Engagement with partisan Russian troll tweets during the 2016 U.S. presidential election
Operatives working for the Russian Internet Research Agency (IRA) infiltrated social media with the goal of disrupting the 2016 U.S. presidential election. We investigate how these operatives or “trolls” leveraged partisan political identities in discussing presidential candidates and parties on Twitter. Adopting a social identity lens, we conceptualize retweeting troll content as a form of identity performance and examine the message properties …
Engagement with incivility in tweets from and directed at local elected officials
Although social media have created novel opportunities for the public and local elected officials representing city or state governments to interact, concerns have been raised about the tenor of their discourse. We used machine learning in this project to identify the presence of incivility in tweets (N = 38,218) made by and directed at local officials representing a metropolitan area over an 18-month period and examine its implications. Compared…
Tipping the Twitter vs. News Media Scale? Conducting a Third Assessment of Intermedia Agenda-Setting Effects during the Presidential Nomination Season
Two previous studies investigated the relationship between newspaper issue agendas and those of candidate and campaign Twitter feeds during the presidential nomination seasons in 2012 and 2016. Both found the intermedia agenda-setting power resided with newspapers. This study replicates the previous two by examining the issue agendas of the nation’s top newspapers and those of candidate and campaign Twitter feeds during the 2020 presidential nomi…
Social Norms and the Dynamics of Online Incivility
Online discussions are performed in the gaze of fellow users. To increase engagement, platforms typically let these users evaluate the comments made by others through rating systems (e.g., via Likes or Down/Up votes). Understanding how such ratings shape, and are shaped by, features of the underlying discussion is important for our understanding of online behavior. In this study, we focus on an increasingly concerning aspect of online discussions…
Notes from the Editors
veryone knows that social media can be an "outrage machine": a dark hole of blistering criticism and rejection that fosters "compare and despair" syndrome by inviting us to judge our inner selves against others' Instagram pics (Haidt and Twenge 2021). However, it also has the potential to connect people in new and dynamic ways, helping to build community across distance and difference
Assessing the Russian Troll Efforts to Sow Discord on Twitter during the 2016 U.S. Election
Although experts agree that the Russian Internet Research Agency deployed trolls on Twitter to disrupt the 2016 U.S. presidential election, questions remain about the nuances of their efforts. We examined almost 350,000 original tweets made during the two-year electoral cycle to investigate the emphasis, timing, content, and partisanship of the trolls’ efforts targeting leading candidates. Despite only dedicating a fraction of their tweets to can…
Social Media Influence and Electoral Competition
Do social media platforms help or hinder democracy? Internet enthusiasts posit that social media could have a democratizing effect by lowering the costs of promotion, while skeptics argue that these platforms replicate or even exacerbate preexisting inequalities. We inform this debate by combining campaign finance and electoral outcome data from the Federal Election Commission with Twitter metrics of candidates who ran in the 2016 U.S. congressio…
Sorting the News
Most people receive political news from social media platforms. Unlike traditional media, these platforms algorithmically determine the order in which news is presented, in part relying on an article's popularity (i.e. number of likes, shares, and comments) to determine its ranking. To what extent does sorting the news by popularity influence people's attitudes toward politics? With two large, nationally representative samples of adults and a nov…
How Algorithms Discriminate Based on Data They Lack
Organizations often employ data-driven models to inform decisions that can have a significant impact on people's lives (e.g., university admissions, hiring). In order to protect people's privacy and prevent discrimination, these decision-makers may choose to delete or avoid collecting social category data, like sex and race. In this article, we argue that such censoring can exacerbate discrimination by making biases more difficult to detect. We b…
Twitter Influencers in the 2016 US Congressional Races
In this paper, I outline a method for collecting Twitter data to identify two types of political actors that are increasingly prominent in social media environments: influential politicians and politicized influencers. Influential politicians are those whose messages are readily retweeted (i.e., shared) while politicized influencers are users who retweet politicians’ messages and who themselves receive many retweets. I find that highly retweeted …
The Effect of Network Structure on Preference Formation
How does network structure influence opinion? Relying on theories of preference formation and social networks, we randomize a sample of adults into networks that vary in structure. In one (a clustered lattice), individuals' connections tend to be connected to each other; in another (a random network), individuals' connections tend not to be connected, instead providing access to different regions of the network. We seed messages that reflect comp…
Social Norms and the Dynamics of Online Incivility
Online discussions are performed in the gaze of fellow users. To increase engagement, platforms typically let these users evaluate the comments made by others through rating systems (e.g., via Likes or Down/Up votes). Understanding how such ratings shape, and are shaped by, features of the underlying discussion is important for our understanding of online behavior. In this study, we focus on an increasingly concerning aspect of online discussions…
Sorting the News
Most people receive political news from social media platforms. Unlike traditional media, these platforms algorithmically determine the order in which news is presented, in part relying on an article's popularity (i.e. number of likes, shares, and comments) to determine its ranking. To what extent does sorting the news by popularity influence people's attitudes toward politics? With two large, nationally representative samples of adults and a nov…
The Effect of Network Structure on Preference Formation
How does network structure influence opinion? Relying on theories of preference formation and social networks, we randomize a sample of adults into networks that vary in structure. In one (a clustered lattice), individuals' connections tend to be connected to each other; in another (a random network), individuals' connections tend not to be connected, instead providing access to different regions of the network. We seed messages that reflect comp…
Social Media Influence and Electoral Competition
Do social media platforms help or hinder democracy? Internet enthusiasts posit that social media could have a democratizing effect by lowering the costs of promotion, while skeptics argue that these platforms replicate or even exacerbate preexisting inequalities. We inform this debate by combining campaign finance and electoral outcome data from the Federal Election Commission with Twitter metrics of candidates who ran in the 2016 U.S. congressio…
How Algorithms Discriminate Based on Data They Lack
Organizations often employ data-driven models to inform decisions that can have a significant impact on people's lives (e.g., university admissions, hiring). In order to protect people's privacy and prevent discrimination, these decision-makers may choose to delete or avoid collecting social category data, like sex and race. In this article, we argue that such censoring can exacerbate discrimination by making biases more difficult to detect. We b…
Twitter Influencers in the 2016 US Congressional Races
In this paper, I outline a method for collecting Twitter data to identify two types of political actors that are increasingly prominent in social media environments: influential politicians and politicized influencers. Influential politicians are those whose messages are readily retweeted (i.e., shared) while politicized influencers are users who retweet politicians’ messages and who themselves receive many retweets. I find that highly retweeted …
Engagement with incivility in tweets from and directed at local elected officials
Although social media have created novel opportunities for the public and local elected officials representing city or state governments to interact, concerns have been raised about the tenor of their discourse. We used machine learning in this project to identify the presence of incivility in tweets (N = 38,218) made by and directed at local officials representing a metropolitan area over an 18-month period and examine its implications. Compared…
Assessing the Russian Troll Efforts to Sow Discord on Twitter during the 2016 U.S. Election
Although experts agree that the Russian Internet Research Agency deployed trolls on Twitter to disrupt the 2016 U.S. presidential election, questions remain about the nuances of their efforts. We examined almost 350,000 original tweets made during the two-year electoral cycle to investigate the emphasis, timing, content, and partisanship of the trolls’ efforts targeting leading candidates. Despite only dedicating a fraction of their tweets to can…
The Effect of Network Structure on Preference Formation
How does network structure influence opinion? Relying on theories of preference formation and social networks, we randomize a sample of adults into networks that vary in structure. In one (a clustered lattice), individuals' connections tend to be connected to each other; in another (a random network), individuals' connections tend not to be connected, instead providing access to different regions of the network. We seed messages that reflect comp…
How Algorithms Discriminate Based on Data They Lack
Organizations often employ data-driven models to inform decisions that can have a significant impact on people's lives (e.g., university admissions, hiring). In order to protect people's privacy and prevent discrimination, these decision-makers may choose to delete or avoid collecting social category data, like sex and race. In this article, we argue that such censoring can exacerbate discrimination by making biases more difficult to detect. We b…
Twitter Influencers in the 2016 US Congressional Races
In this paper, I outline a method for collecting Twitter data to identify two types of political actors that are increasingly prominent in social media environments: influential politicians and politicized influencers. Influential politicians are those whose messages are readily retweeted (i.e., shared) while politicized influencers are users who retweet politicians’ messages and who themselves receive many retweets. I find that highly retweeted …
Social Media Influence and Electoral Competition
Do social media platforms help or hinder democracy? Internet enthusiasts posit that social media could have a democratizing effect by lowering the costs of promotion, while skeptics argue that these platforms replicate or even exacerbate preexisting inequalities. We inform this debate by combining campaign finance and electoral outcome data from the Federal Election Commission with Twitter metrics of candidates who ran in the 2016 U.S. congressio…
Sorting the News
Most people receive political news from social media platforms. Unlike traditional media, these platforms algorithmically determine the order in which news is presented, in part relying on an article's popularity (i.e. number of likes, shares, and comments) to determine its ranking. To what extent does sorting the news by popularity influence people's attitudes toward politics? With two large, nationally representative samples of adults and a nov…
Social Norms and the Dynamics of Online Incivility
Online discussions are performed in the gaze of fellow users. To increase engagement, platforms typically let these users evaluate the comments made by others through rating systems (e.g., via Likes or Down/Up votes). Understanding how such ratings shape, and are shaped by, features of the underlying discussion is important for our understanding of online behavior. In this study, we focus on an increasingly concerning aspect of online discussions…
Notes from the Editors
veryone knows that social media can be an "outrage machine": a dark hole of blistering criticism and rejection that fosters "compare and despair" syndrome by inviting us to judge our inner selves against others' Instagram pics (Haidt and Twenge 2021). However, it also has the potential to connect people in new and dynamic ways, helping to build community across distance and difference
Assessing the Russian Troll Efforts to Sow Discord on Twitter during the 2016 U.S. Election
Although experts agree that the Russian Internet Research Agency deployed trolls on Twitter to disrupt the 2016 U.S. presidential election, questions remain about the nuances of their efforts. We examined almost 350,000 original tweets made during the two-year electoral cycle to investigate the emphasis, timing, content, and partisanship of the trolls’ efforts targeting leading candidates. Despite only dedicating a fraction of their tweets to can…
Tipping the Twitter vs. News Media Scale? Conducting a Third Assessment of Intermedia Agenda-Setting Effects during the Presidential Nomination Season
Two previous studies investigated the relationship between newspaper issue agendas and those of candidate and campaign Twitter feeds during the presidential nomination seasons in 2012 and 2016. Both found the intermedia agenda-setting power resided with newspapers. This study replicates the previous two by examining the issue agendas of the nation’s top newspapers and those of candidate and campaign Twitter feeds during the 2020 presidential nomi…
Engagement with partisan Russian troll tweets during the 2016 U.S. presidential election
Operatives working for the Russian Internet Research Agency (IRA) infiltrated social media with the goal of disrupting the 2016 U.S. presidential election. We investigate how these operatives or “trolls” leveraged partisan political identities in discussing presidential candidates and parties on Twitter. Adopting a social identity lens, we conceptualize retweeting troll content as a form of identity performance and examine the message properties …
Engagement with incivility in tweets from and directed at local elected officials
Although social media have created novel opportunities for the public and local elected officials representing city or state governments to interact, concerns have been raised about the tenor of their discourse. We used machine learning in this project to identify the presence of incivility in tweets (N = 38,218) made by and directed at local officials representing a metropolitan area over an 18-month period and examine its implications. Compared…
Examining the Dynamics of Uncivil Discourse Between Sub-National Political Officials and the Public on Twitter
Despite agreement about the challenges posed by incivility for democratic discourse, much remains to be learned about how incivility manifests in interactions between the public and political elites. We examine the connections between top-down and bottom-up incivility among 22 local and state elected officials and the public over an 18-month period on Twitter. Our analyses show that incivility in a tweet from an elected official significantly inc…
Incivility in Online Discussion as a Collective Phenomenon
Drawing from dynamic systems theory, we examine how incivility is collectively constructed in an online discussion community. Using secondary data consisting of comments shared over a 3-week period to an online news community, we identified three sequences that reflect collective incivility practices. Whereas the persistent incivility sequence included a large proportion of uncivil comments, incivility occurred infrequently in the sporadic incivi…
Social Media and Politics (11 works) · Political science (10 works) · Law (8 works) · Computer Science (7 works) · Law (7 works) · Politics (7 works) · Public relations (7 works) · Social media (7 works) · Sociology (7 works) · Business (6 works)