Journal of Quantitative Description: Digital Media <p>The journal publishes quantitative descriptive social science. It does not publish research that makes causal claims. The journal focuses on evidence that speaks to some substantive question or trend about digital communication processes and media. Articles can use a variety of data types and methods.</p> University of Zurich en-US Journal of Quantitative Description: Digital Media 2673-8813 Characterizing the Reaction of Doctors to COVID-19 on Twitter <p>With the surge of the Delta variant of COVID-19, clear public health messaging on social media has become more vital than ever. We demonstrate how unique Twitter data can be used to explore doctors’ reactions to the early months of the COVID-19 pandemic. We elucidate how discussion differed across locations, over time, and in comparison to non-doctors. Tweets spiked surrounding major events and in locations with rising case numbers. Discussion from doctors initially focused on the origin of the virus in Wuhan, later switching to calls to “stay home.” Doctors tweeted more often about public health and healthcare workers, whereas non-doctors were more likely to tweet about political topics, including China and the Trump administration. The differences in how doctors and non-doctors engage about COVID-19 can provide insight into the similarities and differences in communication between medical experts and the public. Future public health communications may benefit from analyses that compare the social media messages promulgated by various groups.</p> Katie Hsia Edward Kong Copyright (c) 2022 Katie Hsia, Edward Kong 2022-04-20 2022-04-20 2 10.51685/jqd.2022.012 What Circulates on Partisan WhatsApp in India? Insights from an Unusual Dataset <p><span dir="ltr" style="left: 253.359px; top: 861.329px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999308);">In countries ranging from the Philippines </span><span dir="ltr" style="left: 626.895px; top: 861.329px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999501);">to Brazil, political actors have </span><span dir="ltr" style="left: 180px; top: 887.777px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999299);">embraced WhatsApp. In India, WhatsApp groups backed </span><span dir="ltr" style="left: 689.17px; top: 887.777px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999454);">by political parties are </span><span dir="ltr" style="left: 180px; top: 914.225px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999334);">suspected of conveying misinformation and/or of circulating </span><span dir="ltr" style="left: 710.273px; top: 914.225px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999068);">hateful content </span><span dir="ltr" style="left: 180px; top: 940.673px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999356);">pointed towards minority groups, potentially leading </span><span dir="ltr" style="left: 640.264px; top: 940.673px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.997142);">to offline violence. </span><span dir="ltr" style="left: 805.195px; top: 940.673px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999061);">They are </span><span dir="ltr" style="left: 180px; top: 967.12px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999139);">also seen as one of the reasons for the dominance </span><span dir="ltr" style="left: 634.736px; top: 967.12px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999213);">of the ruling party (the BJP). </span><span dir="ltr" style="left: 180px; top: 993.568px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.99934);">Yet, despite this narrative, we so far know little</span><span dir="ltr" style="left: 595.02px; top: 993.568px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999005);">about the content shared on these </span><span dir="ltr" style="left: 180px; top: 1020.02px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999318);">partisan groups nor about the way in which (mis-)information</span><span dir="ltr" style="left: 721.357px; top: 1020.02px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999315);">circulates on them. </span><span dir="ltr" style="left: 180px; top: 1046.46px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999323);">In this manuscript, we describe the visual content </span><span dir="ltr" style="left: 621.328px; top: 1046.46px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999165);">of 533 closed threads </span><span dir="ltr" style="left: 180px; top: 1072.91px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999242);">maintained by party workers across the state of Uttar </span><span dir="ltr" style="left: 653.535px; top: 1072.91px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999337);">Pradesh, collected over a</span><span dir="ltr" style="left: 180px; top: 1099.36px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999107);">period of 9 months. Manual coding of around 36,000 </span><span dir="ltr" style="left: 649.209px; top: 1099.36px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.99955);">images allows us to </span><span dir="ltr" style="left: 180px; top: 1125.81px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.99918);">estimate the amount of misinformation/hateful content </span><span dir="ltr" style="left: 668.027px; top: 1125.81px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.998951);">on one hand, and </span><span dir="ltr" style="left: 180px; top: 1152.25px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999029);">partisan content on the other</span><span dir="ltr" style="left: 433.516px; top: 1152.25px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.993507);">. Additional matching</span><span dir="ltr" style="left: 624.736px; top: 1152.25px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999223);"> of this data with other sources </span><span dir="ltr" style="left: 180px; top: 1178.7px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999325);">and analyses based on computer vision techniques in</span><span dir="ltr" style="left: 660.303px; top: 1178.7px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999337);">turn allows us to evaluate </span><span dir="ltr" style="left: 180px; top: 124.093px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999171);">the extent to which the content posted on WhatsApp threads may serve the </span><span dir="ltr" style="left: 180px; top: 150.541px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999146);">interests of the ruling party</span><span dir="ltr" style="left: 404.189px; top: 150.541px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.993961);">. Analyses suggest that </span><span dir="ltr" style="left: 616.533px; top: 150.541px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999221);">partisan threads contain </span><span dir="ltr" style="left: 180px; top: 176.989px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999346);">relatively few hateful or misinformed posts; more </span><span dir="ltr" style="left: 614.609px; top: 176.989px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999465);">surprisingly maybe, most </span><span dir="ltr" style="left: 180px; top: 203.436px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.99933);">content cannot easily be classified as “partisan”. </span><span dir="ltr" style="left: 611.338px; top: 203.436px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999168);">While much content </span><span dir="ltr" style="left: 180px; top: 229.884px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999389);">appears to be religion-related, which may serve an indirect </span><span dir="ltr" style="left: 635.781px; top: 229.884px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999262);">partisan role, the</span><span dir="ltr" style="left: 180px; top: 256.332px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999214);"> largest share </span><span dir="ltr" style="left: 595.801px; top: 256.332px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.99916);">of the content is </span><span dir="ltr" style="left: 180px; top: 282.78px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.99946);">more easily classifiable </span><span dir="ltr" style="left: 626.885px; top: 282.78px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999309);">as phatic</span><span dir="ltr" style="left: 180px; top: 309.227px; font-size: 20px; font-family: sans-serif; transform: scaleX(0.999141);"> or entertainment related.</span></p> Simon Chauchard Kiran Garimella Copyright (c) 2022 Simon Chauchard, Kiran Garimella 2022-03-02 2022-03-02 2 10.51685/jqd.2022.006 The politicization of medical preprints on Twitter during the early stages of COVID-19 pandemic <p><span style="font-weight: 400;">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.</span></p> Aleksandra Urman Stefania Ionescu David Garcia Anikó Hannák Copyright (c) 2022 Aleksandra Urman, Stefania Ionescu, David Garcia, Anikó Hannák 2022-02-08 2022-02-08 2 10.51685/jqd.2022.003 The Social, Civic, and Political Uses of Instagram in Four Countries <p>Instagram has more than 1 billion monthly users. Yet, little is known about how citizens engage with this platform. We use survey data (representative on age and gender) to examine citizens’ Instagram use 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). Across the four countries, about 40% of respondents used Instagram. This platform is especially popular among young adults who cultivate larger networks compared to older adults. Compared to older adults who use Instagram, younger users are more likely to follow a news organization. We employ these usage patterns to infer different motivations for use, drawing on the uses and gratification approach. We find that this approach is most useful for understanding cross-national and gender differences. In particular, Americans cultivate larger social networks on Instagram compared to citizens from other countries, implying greater social interaction motives. Males are more likely to follow news organizations compared to females, which implies they have more informational motives for Instagram use. Socioeconomic differences in Instagram adoption and types of uses are much smaller than the differences marked by age, gender, and country. This paper establishes the importance of Instagram use among citizens in four Western countries. Furthermore, we offer insights into the segments of the population that are intense users of Instagram, as well as different motivations for use.</p> Shelley Boulianne Christian P. Hoffmann Copyright (c) 2022 Shelley Boulianne, Christian P. Hoffmann 2022-01-09 2022-01-09 2 10.51685/jqd.2022.001 Tweeting on Presidential Coattails: Congressional Candidate Use of Twitter in the 2020 Elections <p>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.</p> Evan Crawford Mikaela Foehr Nathaniel Yee Copyright (c) 2022 Evan Crawford, Mikaela Foehr, Nathaniel Yee 2022-03-11 2022-03-11 2 10.51685/jqd.2022.008 Hate speech’s double damage: A semi-automated approach toward direct and indirect targets <p>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.</p> Mario Haim Elisa Hoven Copyright (c) 2022 Mario Haim, Elisa Hoven 2022-03-07 2022-03-07 2 10.51685/jqd.2022.009 Five Hundred Days of Farsi Twitter <p>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.</p> Layla Hashemi Steven Wilson Constanza Sanhueza Copyright (c) 2022 Layla Hashemi, Steven Wilson, Constanza Sanhueza 2022-04-14 2022-04-14 2 10.51685/jqd.2022.005 If a Tree Falls in the Forest: Presidential Press Conferences and Early Media Narratives about the COVID-19 Crisis <p>Throughout the COVID-19 crisis, as we confronted questions about social distancing, masking wearing, and vaccines, public safety experts warned that the consequences of a misinformed population would be particularly dire due to the serious nature of the threat and necessity of severe collective action to keep the population safe. Thus, the media and the political elites (e.g., President of the United States) who possess the power to set the information agenda around COVID-19 bear a huge responsibility for the general welfare. Through automated text analysis of complete transcripts of national cable, network, and local news, we explore their narratives surrounding the COVID-19 pandemic and we characterize the differences in which topics were covered and how they were covered by various media sources. Our analysis reveals polarized narratives around blame, racial and economic disparities, and scientific conclusions about COVID-19. Among the various agenda-setting mechanisms available to the president is daily press conferences, which provide a unique opportunity to leverage public exposure, accelerated by the state of crisis. We found both resonance and contrast between the narratives of media and President press conferences. However, as online search data revealed, public information-seeking behavior resemble media coverage more than the President's messages.</p> Masha Krupenkin Kai Zhu Dylan Walker David Rothschild Copyright (c) 2022 Masha Krupenkin, Kai Zhu, Dylan Walker, David Rothschild 2022-05-01 2022-05-01 2 10.51685/jqd.2022.011 Fame and Ultrafame: Measuring and comparing daily levels of ‘being talked about’ for United States’ presidents, their rivals, God, countries, and K-pop. <div class="page" title="Page 1"> <div class="layoutArea"> <div class="column"> <p>When building a global brand of any kind—a political actor, clothing style, or belief system— developing widespread awareness is a primary goal. Short of knowing any of the stories or products of a brand, being talked about in whatever fashion—raw fame—is, as Oscar Wilde would have it, better than not being talked about at all. Here, we measure, examine, and contrast the day-to-day raw fame dynamics on Twitter for US Presidents and major US Presidential candidates from 2008 to 2020: Barack Obama, John McCain, Mitt Romney, Hillary Clinton, Donald Trump, and Joe Biden. We assign “lexical fame” to be the number and (Zipfian) rank of the (lowercased) mentions made for each individual across all languages. We show that all five political figures have at some point reached extraordinary volume levels of what we define to be “lexical ultrafame”: An overall rank of approximately 300 or less which is largely the realm of function words and demarcated by the highly stable rank of ‘god’. By this measure, ‘trump’ has become enduringly ultrafamous, from the 2016 election on. We use typical ranks for country names and function words as standards to improve perception of scale. We quantify relative fame rates and find that in the eight weeks leading up the 2008 and 2012 elections, ‘obama’ held a 1000:757 volume ratio over ‘mccain’ and 1000:892 over ‘romney’, well short of the 1000:544 and 1000:504 volumes favoring ‘trump’ over ‘hillary’ and ‘biden’ in the 8 weeks leading up to the 2016 and 2020 elections. Finally, we track how only one other entity has more sustained ultrafame than ‘trump’ on Twitter: The K-pop (Korean pop) band BTS. We chart the dramatic rise of BTS, finding their Twitter handle ‘@bts twt’ has been able to compete with ‘a’ and ‘the’, reaching a rank of three at the day scale and a rank of one at the quarter-hour scale. Our findings for BTS more generally point to K-pop’s growing economic, social, and political power.</p> </div> </div> </div> Peter Dodds Joshua Minot Michael Arnold Thayer Alshaabi Jane Adams David Dewhurst Andrew Reagan Christopher Danforth Copyright (c) 2022 Peter Dodds, Joshua Minot, Michael Arnold, Thayer Alshaabi, Jane Adams, David Dewhurst, Andrew Reagan, Christopher Danforth 2022-02-27 2022-02-27 2 10.51685/jqd.2022.004 A Note on Increases in Inattentive Online Survey-Takers Since 2020 <p>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.</p> John Ternovski Lilla Orr Copyright (c) 2022 John Ternovski, Lilla Orr, Joshua Kalla, Peter Aronow 2022-02-07 2022-02-07 2 10.51685/jqd.2022.002 Googling for Abortion: Search Engine Mediation of Abortion Accessibility in the United States <p>Among the myriad barriers to abortion access, crisis pregnancy centers (CPCs) pose an additional difficulty by targeting women with unexpected or “crisis” pregnancies in order to dissuade them from the procedure. Web search engines may prove to be another barrier, being in a powerful position to direct their users to health information, and above all, health services. In this study we ask, to what degree does Google Search provide quality responses to users searching for an abortion provider, specifically in terms of directing them to abortion clinics (ACs) or CPCs. To answer this question, we considered the scenario of a woman searching for abortion services online, and conducted 10 abortion-related queries from 467 locations across the United States once a week for 14 weeks. Overall, among Google’s location results that feature businesses alongside a map, 79.4% were ACs, and 6.9% were CPCs. When an AC was returned, it was the closest known AC location 86.9% of the time. However, when a CPC appeared in a result set, it was the closest one to the search location 75.9% of the time. Examining correlates of AC results, we found that fewer AC results were returned for searches from poorer and rural areas, and those with TRAP laws governing AC facility and clinician requirements. We also observed that Google’s performance on our queries significantly improved following a major algorithm update. These results have important implications concerning health access quality and equity, both for individual users and public health policy.</p> Yelena Mejova Tatiana Gracyk Ronald E. Robertson Copyright (c) 2022 Yelena Mejova, Tatiana Gracyk, Ronald Robertson 2022-02-23 2022-02-23 2 10.51685/jqd.2022.007