International media was quick to dub the Iranian Green Movement a “Twitter revolution” when it erupted in the summer of 2009. State violence against protestors was captured in real time and broadcast worldwide on social media, providing an early example of a regime's helplessness at locking down a narrative in the face of ubiquitous smart phones. Over a decade later, nearly all foreign social media remain officially blocked in Iran, yet Iranians evade state suppression and remain connected to the global community. This article introduces a new dataset of all Farsi-language tweets since September 2019. To date, this amounts to the full text and associated metadata of over 500 million tweets and the evidence shows that the overwhelming majority of this content originates from within the borders of Iran. The study describes the scope of Iran's continued connection to the global community via Twitter, descriptively explores the content of that social media, evaluates what this means for Iranian politics and society, and explores its broader implications for researchers in the age of social media. In particular, we argue that the demonstrated ability to collect the voices of citizens, even from one of the most repressive digital regimes in the world, provides an invaluable framework for scholars with even minimal resources to undertake large-scale digital ethnography.
{"title":"Five Hundred Days of Farsi Twitter","authors":"Layla Hashemi, Steven Wilson, C. Sanhueza","doi":"10.51685/jqd.2022.005","DOIUrl":"https://doi.org/10.51685/jqd.2022.005","url":null,"abstract":"International media was quick to dub the Iranian Green Movement a “Twitter revolution” when it erupted in the summer of 2009. State violence against protestors was captured in real time and broadcast worldwide on social media, providing an early example of a regime's helplessness at locking down a narrative in the face of ubiquitous smart phones. Over a decade later, nearly all foreign social media remain officially blocked in Iran, yet Iranians evade state suppression and remain connected to the global community. This article introduces a new dataset of all Farsi-language tweets since September 2019. To date, this amounts to the full text and associated metadata of over 500 million tweets and the evidence shows that the overwhelming majority of this content originates from within the borders of Iran. The study describes the scope of Iran's continued connection to the global community via Twitter, descriptively explores the content of that social media, evaluates what this means for Iranian politics and society, and explores its broader implications for researchers in the age of social media. In particular, we argue that the demonstrated ability to collect the voices of citizens, even from one of the most repressive digital regimes in the world, provides an invaluable framework for scholars with even minimal resources to undertake large-scale digital ethnography.","PeriodicalId":93587,"journal":{"name":"Journal of quantitative description: digital media","volume":"90 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90691159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
There is a long history of political science research focused on congressional candidates riding presidential coattails into office. The underlying theory for this potential relationship is relatively simple—when presidential nominees are popular, they can help bolster the electoral fortunes of their down-ballot, co-partisan candidates. If this is right, congressional candidates should be incentivized to publicly align themselves with their co-partisan presidential nominee, albeit in strategic ways. We look for this relationship by constructing an original dataset of congressional candidate Twitter data and identifying the extent to which candidates mention presidential nominees during the 2020 campaign, a behavior we call “tweeting on coattails.” Our data allow us to describe relationships between “tweeting on coattails”, candidate party ID, and district-level electoral conditions. We find that overall, challengers tweeted more than incumbents, but incumbents were more likely to “tweet on coattails.” In addition, candidates of both parties “tweeted on coattails” more frequently if they were running in a district where their party’s nominee is popular. This relationship was not symmetric in magnitude, however, as Republicans were significantly more likely to tweet about Donald Trump than Democrats were to tweet about Joe Biden.
{"title":"Tweeting on Presidential Coattails: Congressional Candidate Use of Twitter in the 2020 Elections","authors":"Evan Crawford, Mikaela Foehr, Nathaniel Yee","doi":"10.51685/jqd.2022.008","DOIUrl":"https://doi.org/10.51685/jqd.2022.008","url":null,"abstract":"There is a long history of political science research focused on congressional candidates riding presidential coattails into office. The underlying theory for this potential relationship is relatively simple—when presidential nominees are popular, they can help bolster the electoral fortunes of their down-ballot, co-partisan candidates. If this is right, congressional candidates should be incentivized to publicly align themselves with their co-partisan presidential nominee, albeit in strategic ways. We look for this relationship by constructing an original dataset of congressional candidate Twitter data and identifying the extent to which candidates mention presidential nominees during the 2020 campaign, a behavior we call “tweeting on coattails.” Our data allow us to describe relationships between “tweeting on coattails”, candidate party ID, and district-level electoral conditions. We find that overall, challengers tweeted more than incumbents, but incumbents were more likely to “tweet on coattails.” In addition, candidates of both parties “tweeted on coattails” more frequently if they were running in a district where their party’s nominee is popular. This relationship was not symmetric in magnitude, however, as Republicans were significantly more likely to tweet about Donald Trump than Democrats were to tweet about Joe Biden.","PeriodicalId":93587,"journal":{"name":"Journal of quantitative description: digital media","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73858866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Democracies around the world have been facing increasing challenges with hate speech online as it contributes to a tense and thus less discursive public sphere. In that, hate speech online targets free speech both directly and indirectly, through harassments and explicit harm as well as by informing a vicious environment of irrationality, misrepresentation, or disrespect. Consequently, platforms have implemented varying means of comment-moderation techniques, depending both on policy regulations and on the quantity and quality of hate speech online. This study seeks to provide descriptive measures between direct and indirect targets in light of different incentives and practices of moderation on both social media and news outlets. Based on three distinct samples from German Twitter, YouTube, and a set of four news outlets, it applies semi-automated content analyses using a set of five cross-sample classifiers. Thereby, the largest amounts of visible hate speech online depict rather implicit devaluations of ideas or behavior. More explicit forms of hate speech online, such as insult, slander, or vulgarity, are only rarely observable and accumulate around certain events (Twitter) or single videos (YouTube). Moreover, while hate speech on Twitter and YouTube tends to target particular groups or individuals, hate speech below news articles shows a stronger focus on debates. Potential reasons and implications are discussed in light of political and legal efforts in Germany.
{"title":"Hate speech’s double damage: A semi-automated approach toward direct and indirect targets","authors":"Mario Haim, E.v. Hoven","doi":"10.51685/jqd.2022.009","DOIUrl":"https://doi.org/10.51685/jqd.2022.009","url":null,"abstract":"Democracies around the world have been facing increasing challenges with hate speech online as it contributes to a tense and thus less discursive public sphere. In that, hate speech online targets free speech both directly and indirectly, through harassments and explicit harm as well as by informing a vicious environment of irrationality, misrepresentation, or disrespect. Consequently, platforms have implemented varying means of comment-moderation techniques, depending both on policy regulations and on the quantity and quality of hate speech online. This study seeks to provide descriptive measures between direct and indirect targets in light of different incentives and practices of moderation on both social media and news outlets. Based on three distinct samples from German Twitter, YouTube, and a set of four news outlets, it applies semi-automated content analyses using a set of five cross-sample classifiers. Thereby, the largest amounts of visible hate speech online depict rather implicit devaluations of ideas or behavior. More explicit forms of hate speech online, such as insult, slander, or vulgarity, are only rarely observable and accumulate around certain events (Twitter) or single videos (YouTube). Moreover, while hate speech on Twitter and YouTube tends to target particular groups or individuals, hate speech below news articles shows a stronger focus on debates. Potential reasons and implications are discussed in light of political and legal efforts in Germany.","PeriodicalId":93587,"journal":{"name":"Journal of quantitative description: digital media","volume":"17 3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83684408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In countries ranging from the Philippines to Brazil, political actors have embraced WhatsApp. In India, WhatsApp groups backed by political parties are suspected of conveying misinformation and/or of circulating hateful content pointed towards minority groups, potentially leading to offline violence. They are also seen as one of the reasons for the dominance of the ruling party (the BJP). Yet, despite this narrative, we so far know littleabout the content shared on these partisan groups nor about the way in which (mis-)informationcirculates on them. In this manuscript, we describe the visual content of 533 closed threads maintained by party workers across the state of Uttar Pradesh, collected over aperiod of 9 months. Manual coding of around 36,000 images allows us to estimate the amount of misinformation/hateful content on one hand, and partisan content on the other. Additional matching of this data with other sources and analyses based on computer vision techniques inturn allows us to evaluate the extent to which the content posted on WhatsApp threads may serve the interests of the ruling party. Analyses suggest that partisan threads contain relatively few hateful or misinformed posts; more surprisingly maybe, most content cannot easily be classified as “partisan”. While much content appears to be religion-related, which may serve an indirect partisan role, the largest share of the content is more easily classifiable as phatic or entertainment related.
{"title":"What Circulates on Partisan WhatsApp in India? Insights from an Unusual Dataset","authors":"Simon Chauchard, Kiran Garimella","doi":"10.51685/jqd.2022.006","DOIUrl":"https://doi.org/10.51685/jqd.2022.006","url":null,"abstract":"In countries ranging from the Philippines to Brazil, political actors have embraced WhatsApp. In India, WhatsApp groups backed by political parties are suspected of conveying misinformation and/or of circulating hateful content pointed towards minority groups, potentially leading to offline violence. They are also seen as one of the reasons for the dominance of the ruling party (the BJP). Yet, despite this narrative, we so far know littleabout the content shared on these partisan groups nor about the way in which (mis-)informationcirculates on them. In this manuscript, we describe the visual content of 533 closed threads maintained by party workers across the state of Uttar Pradesh, collected over aperiod of 9 months. Manual coding of around 36,000 images allows us to estimate the amount of misinformation/hateful content on one hand, and partisan content on the other. Additional matching of this data with other sources and analyses based on computer vision techniques inturn allows us to evaluate the extent to which the content posted on WhatsApp threads may serve the interests of the ruling party. Analyses suggest that partisan threads contain relatively few hateful or misinformed posts; more surprisingly maybe, most content cannot easily be classified as “partisan”. While much content appears to be religion-related, which may serve an indirect partisan role, the largest share of the content is more easily classifiable as phatic or entertainment related.","PeriodicalId":93587,"journal":{"name":"Journal of quantitative description: digital media","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84962725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We examine the patterns of medical preprint sharing on Twitter during the early stages of the COVID-19 pandemic. Our analysis demonstrates a stark increase in attention to medical preprints among the general public since the beginning of the pandemic. We also observe a political divide in medical preprint sharing patterns - a finding in line with previous observations regarding the politicisation of COVID-19-related discussions. In addition, we find that the increase in attention to preprints from the members of the general public coincided with the change in the social media-based discourse around preprints.
{"title":"The politicization of medical preprints on Twitter during the early stages of COVID-19 pandemic","authors":"A. Urman, Ş. Ionescu, David Garcia, Anikó Hannák","doi":"10.51685/jqd.2022.003","DOIUrl":"https://doi.org/10.51685/jqd.2022.003","url":null,"abstract":"We examine the patterns of medical preprint sharing on Twitter during the early stages of the COVID-19 pandemic. Our analysis demonstrates a stark increase in attention to medical preprints among the general public since the beginning of the pandemic. We also observe a political divide in medical preprint sharing patterns - a finding in line with previous observations regarding the politicisation of COVID-19-related discussions. In addition, we find that the increase in attention to preprints from the members of the general public coincided with the change in the social media-based discourse around preprints.","PeriodicalId":93587,"journal":{"name":"Journal of quantitative description: digital media","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80579463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
John Ternovski, Lilla V. Orr, Joshua L. Kalla, P. Aronow
Lucid, a popular source of online convenience survey samples, has seen a significant increase in inattentive respondents since 2020. Inattentive participants – respondents who incorrectly answer directed query attention check questions – may be introducing substantial measurement error and attenuation bias. Using data from 152,967 survey respondents across multiple studies conducted between January 2020 and June 2021, we find that inattentive respondents report less reliable demographic data, less stable responses, and are systematically different from attentive respondents. We find some evidence of attenuation bias and mixed evidence that data quality has decreased slightly since 2020 even after filtering for inattentive respondents. We conclude that researchers using Lucid should report if they screened on attentiveness and consider replicating any null results. Such an unexpected increase in inattentiveness in a widely-used platform suggests that future researchers relying on online convenience survey samples should continuously assess data quality.
{"title":"A Note on Increases in Inattentive Online Survey-Takers Since 2020","authors":"John Ternovski, Lilla V. Orr, Joshua L. Kalla, P. Aronow","doi":"10.51685/jqd.2022.002","DOIUrl":"https://doi.org/10.51685/jqd.2022.002","url":null,"abstract":"Lucid, a popular source of online convenience survey samples, has seen a significant increase in inattentive respondents since 2020. Inattentive participants – respondents who incorrectly answer directed query attention check questions – may be introducing substantial measurement error and attenuation bias. Using data from 152,967 survey respondents across multiple studies conducted between January 2020 and June 2021, we find that inattentive respondents report less reliable demographic data, less stable responses, and are systematically different from attentive respondents. We find some evidence of attenuation bias and mixed evidence that data quality has decreased slightly since 2020 even after filtering for inattentive respondents. We conclude that researchers using Lucid should report if they screened on attentiveness and consider replicating any null results. Such an unexpected increase in inattentiveness in a widely-used platform suggests that future researchers relying on online convenience survey samples should continuously assess data quality.","PeriodicalId":93587,"journal":{"name":"Journal of quantitative description: digital media","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78158904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Instagram has more than 1 billion monthly users. Yet, little is known about how citizens engage with this platform. In this paper, we use representative survey data to examine social, civic, and political uses of Instagram by citizens in four countries: the United States, Canada, the United Kingdom, and France (n=6,291). The survey was administered to an online panel matched to the age and gender profile of each country (September to November 2019). About 40% of respondents used Instagram. This platform is especially popular among young adults (73%). Users’ network sizes are typically small, as a third of users have less than 15 followers and follow less than 15 other accounts. About 15% of users followed news organizations, a nonprofit organization or charity, or a political candidate or party. While users rarely cultivate networks with ties to these formal organizations and groups, civic and political information flows on this platform. Approximately 57% of users report seeing political information on Instagram during the previous 12 months. These findings suggest political information on Instagram flows through informal rather than formal networks. This paper establishes the importance of social, civic, and political uses of Instagram among citizens in four Western countries. Furthermore, we offer insights into the segments of the population that are intense users of Instagram, which helps to understand the role of this platform in civic and political life.
{"title":"The Social, Civic, and Political Uses of Instagram in Four Countries","authors":"Shelley Boulianne, C. Hoffmann","doi":"10.51685/jqd.2022.001","DOIUrl":"https://doi.org/10.51685/jqd.2022.001","url":null,"abstract":"Instagram has more than 1 billion monthly users. Yet, little is known about how citizens engage with this platform. In this paper, we use representative survey data to examine social, civic, and political uses of Instagram by citizens in four countries: the United States, Canada, the United Kingdom, and France (n=6,291). The survey was administered to an online panel matched to the age and gender profile of each country (September to November 2019). About 40% of respondents used Instagram. This platform is especially popular among young adults (73%). Users’ network sizes are typically small, as a third of users have less than 15 followers and follow less than 15 other accounts. About 15% of users followed news organizations, a nonprofit organization or charity, or a political candidate or party. While users rarely cultivate networks with ties to these formal organizations and groups, civic and political information flows on this platform. Approximately 57% of users report seeing political information on Instagram during the previous 12 months. These findings suggest political information on Instagram flows through informal rather than formal networks. This paper establishes the importance of social, civic, and political uses of Instagram among citizens in four Western countries. Furthermore, we offer insights into the segments of the population that are intense users of Instagram, which helps to understand the role of this platform in civic and political life.","PeriodicalId":93587,"journal":{"name":"Journal of quantitative description: digital media","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84609449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
On YouTube, we found extensive content relating to the recent Venezuelan refugee movement that mostly affects neighboring countries like Peru and Ecuador. While there are several studies on general hate speech on social media, only a few have focused on the online discussion of the Venezuelan migration crisis representing the Latin American perspective. Here, we analyzed via manual coding and computational text analysis 235,251 comments from 200 YouTube videos (selected according to theoretical criteria) in the Spanish language on the Venezuelan refugee crisis. In our sample, we found a high number of problematic comments in videos on Venezuelan refugees and migrants, of which 32% were offensive comments and 20% were hateful comments. The most common linguistic patterns revealed references to xenophobic, racist, and sexist content, and showed that offensive content and hate speech are not easy to separate. Only a small amount of around 8% of highly active users is responsible for about 40% of the problematic content and these users actively comment on multiple videos, indicating a network structure in our sample. Our results enlighten a much-neglected topic in the discussion about Venezuelan refugees and migrants on YouTube and contribute to an enhanced understanding of online hate speech from a Latin American perspective for better and early detection.
{"title":"Problematic Content in Spanish Language Comments in YouTube Videos about Venezuelan Refugees and Migrants","authors":"L. Aguirre, Emese Domahidi","doi":"10.51685/jqd.2021.022","DOIUrl":"https://doi.org/10.51685/jqd.2021.022","url":null,"abstract":"On YouTube, we found extensive content relating to the recent Venezuelan refugee movement that mostly affects neighboring countries like Peru and Ecuador. While there are several studies on general hate speech on social media, only a few have focused on the online discussion of the Venezuelan migration crisis representing the Latin American perspective. Here, we analyzed via manual coding and computational text analysis 235,251 comments from 200 YouTube videos (selected according to theoretical criteria) in the Spanish language on the Venezuelan refugee crisis. In our sample, we found a high number of problematic comments in videos on Venezuelan refugees and migrants, of which 32% were offensive comments and 20% were hateful comments. The most common linguistic patterns revealed references to xenophobic, racist, and sexist content, and showed that offensive content and hate speech are not easy to separate. Only a small amount of around 8% of highly active users is responsible for about 40% of the problematic content and these users actively comment on multiple videos, indicating a network structure in our sample. Our results enlighten a much-neglected topic in the discussion about Venezuelan refugees and migrants on YouTube and contribute to an enhanced understanding of online hate speech from a Latin American perspective for better and early detection.","PeriodicalId":93587,"journal":{"name":"Journal of quantitative description: digital media","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90528069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the rise of social media, everyone has the potential to be both a consumer and producer of online content. As a result, the role that word of mouth plays in news consumption has been dramatically increased. Although one might assume that consumers share news because they believe it to be true, widespread concerns about the spread of misinformation suggest that truthfulness may actually not be a dominant driver of sharing online. Across two studies with 5,000 participants, we investigate what makes news sharable on social media. We find that sharing is positively predicted by two separate factors. One factor does involve the headline’s perceived accuracy, as well as its familiarity. The second, however, involves the headline’s perceived importance and emotional evocativeness. This second factor is negatively associated with the headline’s objective veracity, and less decision weight is put on the second factor by subjects with more cognitive reflection and political knowledge, and by subjects who are less politically conservative. These findings have important implications for news publishers, social media platforms, and society at large.
{"title":"What Makes News Sharable on Social Media?","authors":"Cathy Xi Chen, Gordon Pennycook, David G. Rand","doi":"10.31234/OSF.IO/GZQCD","DOIUrl":"https://doi.org/10.31234/OSF.IO/GZQCD","url":null,"abstract":"With the rise of social media, everyone has the potential to be both a consumer and producer of online content. As a result, the role that word of mouth plays in news consumption has been dramatically increased. Although one might assume that consumers share news because they believe it to be true, widespread concerns about the spread of misinformation suggest that truthfulness may actually not be a dominant driver of sharing online. Across two studies with 5,000 participants, we investigate what makes news sharable on social media. We find that sharing is positively predicted by two separate factors. One factor does involve the headline’s perceived accuracy, as well as its familiarity. The second, however, involves the headline’s perceived importance and emotional evocativeness. This second factor is negatively associated with the headline’s objective veracity, and less decision weight is put on the second factor by subjects with more cognitive reflection and political knowledge, and by subjects who are less politically conservative. These findings have important implications for news publishers, social media platforms, and society at large.","PeriodicalId":93587,"journal":{"name":"Journal of quantitative description: digital media","volume":"104 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87715308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Josephine Lukito, P. Sarma, Jordan M. Foley, Aman Abhishek, E. Bucy, Larissa Doroshenko, Zhongkai Sun, Jon C. W. Pevehouse, W. Sethares, Dhavan V. Shah
Live-tweeting has emerged as a popular hybrid media activity during broadcasted media events. Through second screens, users are able to engage with one another and react in real time to the broadcasted content. These reactions are dynamic: they ebb and flow throughout the media event as users respond to and converse about different memorable moments. Using the first 2016 U.S. presidential debate between Hillary Clinton and Donald Trump as a case, this paper employs a temporal method for identifying resonant moments on social media during televised events by combining time series analysis, qualitative (human-in-the-loop) evaluation, and a novel natural language processing tool to identify discursive shifts before and after resonant moments. This analysis finds key differences in social media discourse about the two candidates. Notably, Trump received substantially more coverage than Clinton throughout the debate. However, a more in-depth analysis of these candidates’ resonant moments reveals that discourse about Trump tended to be more critical compared to discourse associated with Clinton’s resonant moments.
{"title":"Resonant Moments in Media Events:","authors":"Josephine Lukito, P. Sarma, Jordan M. Foley, Aman Abhishek, E. Bucy, Larissa Doroshenko, Zhongkai Sun, Jon C. W. Pevehouse, W. Sethares, Dhavan V. Shah","doi":"10.51685/jqd.2021.019","DOIUrl":"https://doi.org/10.51685/jqd.2021.019","url":null,"abstract":"Live-tweeting has emerged as a popular hybrid media activity during broadcasted media events. Through second screens, users are able to engage with one another and react in real time to the broadcasted content. These reactions are dynamic: they ebb and flow throughout the media event as users respond to and converse about different memorable moments. Using the first 2016 U.S. presidential debate between Hillary Clinton and Donald Trump as a case, this paper employs a temporal method for identifying resonant moments on social media during televised events by combining time series analysis, qualitative (human-in-the-loop) evaluation, and a novel natural language processing tool to identify discursive shifts before and after resonant moments. This analysis finds key differences in social media discourse about the two candidates. Notably, Trump received substantially more coverage than Clinton throughout the debate. However, a more in-depth analysis of these candidates’ resonant moments reveals that discourse about Trump tended to be more critical compared to discourse associated with Clinton’s resonant moments.","PeriodicalId":93587,"journal":{"name":"Journal of quantitative description: digital media","volume":"67 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80051266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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