Social Media Reactions Research Articles

Dehumanization on Twitter in the Turkish–Kurdish conflict

This article examines the dissemination of images of mutilated and humiliated dead bodies of ‘others’ and reactions of Twitter users to these images as dehumanizing practices. When the peace negotiations between the Turkish state and Kurdish PKK failed, numerous images of mutilated and humiliated dead bodies of PKK militants were disseminated by Twitter accounts apparently used by members of the Turkish security forces. The author focuses on two controversial cases from 2015 and immediate social media reactions to those images in order to demonstrate how dehumanization of Kurdish militants played out in the case of Turkey.

#sorrynotsorry: A Teaching Module on Advertising Errors in the Digital Age

Abstract: In this essay, I outline strategies for a teaching module on corporate advertising errors, with a focus on the relationship between social media reactions, corporate apologies, and subsequent responses and long-term effects. I demonstrate how we read five key problematic advertising texts from Abercrombie & Fitch, Pepsi, H&M, Bud Light, Heineken, and Dove in consonance with one another. We then divide up into groups to track the life cycle of the corporate reaction-apology-response scenario in which there is a widespread negative reaction to an ad; the company apologizes and outlines possible steps for change; there is a social media evaluation of the apology; and, in some cases, key individuals involved in the text engage in the discussion. Students are empowered to develop expertise around one case and teach their colleagues, leading to a rich group discussion thinking about these ads together. In the final part of the essay, I briefly discuss a second class session in which we categorize the kinds of transgressions these advertisements embody, from racism to misogyny to anti-Semitism. We use these typologies to gain insight into the relationship between the kinds of errors showcased in ads and the nature of the response to them, thinking both within and across categories.

Fear and Derision: A Quantitative Content Analysis of Provaccine and Antivaccine Internet Memes.

The purpose of the study was to examine the characteristics of Internet memes created and disseminated by proponents and opponents of vaccinations. A quantitative content analysis was performed on 234 pro- and antivaccine memes culled from the vaccination fan pages with the greatest number of followers on Facebook. Coding variables included whether the meme was pro- or antivaccine, percentage of factually incorrect claims, mention of the out-group, persuasive appeals (emotion, fear, and rationality), degree of sarcasm, and number of reactions and shares. The most prevalent themes concerned vaccine-preventable diseases, vaccine injury/safety/autism, and conspiracy theories. Independent t tests indicated that provaccination memes were more likely to use sarcasm whereas antivaccination memes were more likely to contain emotion and fear appeals and inaccurate claims. The percentage veracity of the claims in each meme was fact-checked using authoritative scientific sources. A path analysis applying structural equation modeling revealed that memes containing characteristics that were antivaccine (vs. provaccine), appealed to emotion, and appealed to rationality significantly contributed to greater likelihood of social media reactions and shares. Additional analysis determined that both pro- and antivaccination memes tended to contain more gist than verbatim information, and both groups did not significantly differ on this gist-to-verbatim variable. Findings offer insights to understand the persuasion tactics that provaccine and antivaccine groups apply in memes to persuade others via social media. Understanding these techniques will enable the development of health communication strategies to combat false and damaging vaccine information disseminated on the Internet.

Emergent Sentiment in Financial Markets: Sentiment Flow from Social Media to Mass Media

Mass media sentiment of financial news significantly influences investment decisions of investors. Hence, studying how this sentiment emerges is important. In years past this was straightforward, often dictated by journalists who cover financial news, but this has become more complex now. In this paper we focus on how social media sentiment affects mass media sentiment. Using data from Sina Weibo and Sina Finance (around 60 million weibos and 6.2 million news articles) we show that social media does influence mass media sentiment emergence for financial news. The sentiment consistency between social media reaction and prior news articles amplifies the persistence of mass media sentiment over time. By contrast, we found limited evidence of social media reducing the persistence of mass media sentiment over time. The results have significant implications for understanding how two types of media, treated separately in the literature, may be connected.

Влияние силового подавления протеста на обсуждение протестной акции в социальных сетях

Фокус работы связан с реакцией в социальных сетях на репрессии против протестующих со стороны правоохранительных органов. Будучи практически неисследованной, данная тема рассматривается нами на пересечении двух крупных направлений изучения протестной политики: во-первых, взаимосвязи между репрессиями и протестной активностью и, во-вторых, роли социальных сетей в динамике протеста. Опираясь на анализ существующих теорий, мы предположили, что обсуждение подавленной акции будет более широким и привлечет больше внимания пользователей, чем обсуждение акции, прошедшей мирно. Кроме того, полагаем, что насильственный характер подавления акции протеста будет выводить ее обсуждение за пределы круга политических единомышленников. Для проверки сформулированных гипотез мы обратились к двум протестным акциям, которые имели место с разницей менее чем в неделю и характеризовались пересекающимся составом организаторов, но проходили по принципиально различающимся сценариям. Первая акция, «митинг в защиту интернета» / «митинг против блокировки Telegram» произошла 30 апреля 2018 г. Вторая протестная акция, «Он нам не царь», была приурочена к инаугурации В. Путина на четвертый срок и прошла 5 мая 2018 г. Для исследования были собраны все публично доступные сообщения (оригинальные посты, репосты, комментарии) из социальной сети «ВКонтакте» за период с 29 апреля по 2 мая и с 4 мая по 7 мая 2018 г., содержавшие слово «митинг» в любой форме. Данные были исследованы методами сетевого анализа и описательной статистики. Показано, что акция, подавленная полицией, вызвала более широкое обсуждение в социальных сетях и за счет большего резонанса в комментариях, и за счет более продолжительного и широкого обсуждения в оригинальных постах. Равное число авторов, обсуждавших обе акции, сгенерировало большее число постов про акцию, подавленную полицией. Посты, посвященные обсуждению этой акции, имели большую вероятность вызвать «затратную» реакцию пользователей. Обсуждение акции, подавленной полицией, оказалось более централизованным, а коммуникации вокруг нее — более плотными. Эти результаты подтверждают сформулированные гипотезы. Применение насилия со стороны сил правопорядка способствует как расширению числа активно вовлеченных пользователей, так и углублению взаимодействия между ними и улучшению «качества» их участия.
 Благодарность. Исследование проведено при поддержке РФФИ, проект 18-011-01134 «Динамика развития политической нестабильности: построение теоретической модели и ее эмпирическое тестирование».

Accelerating dynamics of collective attention

With news pushed to smart phones in real time and social media reactions spreading across the globe in seconds, the public discussion can appear accelerated and temporally fragmented. In longitudinal datasets across various domains, covering multiple decades, we find increasing gradients and shortened periods in the trajectories of how cultural items receive collective attention. Is this the inevitable conclusion of the way information is disseminated and consumed? Our findings support this hypothesis. Using a simple mathematical model of topics competing for finite collective attention, we are able to explain the empirical data remarkably well. Our modeling suggests that the accelerating ups and downs of popular content are driven by increasing production and consumption of content, resulting in a more rapid exhaustion of limited attention resources. In the interplay with competition for novelty, this causes growing turnover rates and individual topics receiving shorter intervals of collective attention.

Social media addiction and social media reactions: The implications for job performance

ABSTRACTWe investigate the intersection of social media and the workplace, focusing on job performance impacts of employees’ social media addictions and social media reactions through work–family balance and burnout. The research model is grounded in conservation of resources theory, which suggests social media compulsions and emotional reactions to co-worker’s social media posts will deplete employees’ energetic and constructive resources, making it difficult to achieve work-family balance and increasing the likelihood of job burnout, and will ultimately degrade job performance. A sample of 326 full-time employees revealed a negative relationship between social media addiction and work-family balance and a positive relationship between social media reactions and job burnout. Balance and burnout mediated the relationship between social media and job performance such that social media addiction was negatively related to job performance through work–family balance, and social media reactions were negatively related to performance through burnout and work–family conflict.

Analyzing and Visualizing Emotional Reactions Expressed by Emojis in Location-Based Social Media

Social media platforms such as Twitter are extensively used for expressing and exchanging thoughts, opinions, ideas, and feelings, i.e., reactions concerning a topic or an event. Factual information about an event to which people are reacting can be obtained from different types of (geo-)sensors, official authorities, or the public press. However, these sources hardly reveal the emotional or attitudinal impact of events on people, which is, for example, reflected in their reactions on social media. Two approaches that utilize emojis are proposed to obtain the sentiment and emotions contained in social media reactions. Subsequently, these two approaches, along with visualizations that focus on space, time, and topic, are applied to Twitter reactions in the example case of Brexit.

Public Health Emergency Risk Communication and Social Media Reactions to an Errant Warning of a Ballistic Missile Threat - Hawaii, January 2018.

On January 13, 2018, at 8:07 a.m. Hawaii Standard Time, an errant emergency alert was sent to persons in Hawaii. An employee at the Hawaii Emergency Management Agency (EMA) sent the errant alert via the Wireless Emergency Alert (WEA) system and the Emergency Alert System (EAS) during a ballistic missile preparedness drill, advising persons to seek shelter from an incoming ballistic missile. WEA delivers location-based warnings to wireless carrier systems, and EAS sends alerts via television and radio (1). After 38 minutes, at 8:45 a.m., Hawaii EMA retracted the alert via WEA and EAS (2). To understand the impact of the alert, social media responses to the errant message were analyzed. Data were extracted from Twitter* using a Boolean search for tweets (Twitter postings) posted on January 13 regarding the false alert. Tweets were analyzed during two 38-minute periods: 1) early (8:07-8:45 a.m.), the elapsed time the errant alert circulated until the correction was issued and 2) late (8:46-9:24 a.m.), the same amount of elapsed time after issuance of the correction. A total of 5,880 tweets during the early period and 8,650 tweets during the late period met the search criteria. Four themes emerged during the early period: information processing, information sharing, authentication, and emotional reaction. During the late period, information sharing and emotional reaction themes persisted; denunciation, insufficient knowledge to act, and mistrust of authority also emerged as themes. Understanding public interpretation, sharing, and reaction to social media messages related to emergencies can inform development and dissemination of accurate public health messages to save lives during a crisis.

Argumentation in the 2016 US presidential elections: annotated corpora of television debates and social media reaction

In this paper we present US2016, the largest publicly available set of corpora of annotated dialogical argumentation. The annotation covers argumentative relations, dialogue acts and pragmatic features. The corpora comprise transcriptions of television debates leading up to the 2016 US presidential elections, and reactions to the debates on Reddit.These two constitutive parts of the corpora are integrated by means of the intertextual correspondence between them. The rhetorical richness and high argument density of the communicative context results in cross-genre corpora that are robust resources for the study of the dialogical dynamics of argumentation in three ways: first, in empirical strands of research in discourse analysis and argumentation studies; second,in the burgeoning field of argument mining where automatic techniques require such data; and third, in formulating algorithmic techniques for sensemaking through the development of Argument Analytics.

Online Blaming and Intimate Partner Violence: A Content Analysis of Social Media Comments

Social media has become a ubiquitous form of interacting and sharing information. However, comments on social media sites are often aggressive and contemptuous, especially when topics are controversial or politically charged. For example, discussion of intimate partner violence (IPV) tends to provoke strong reactions from outsiders, who make angry or blaming remarks about those involved. Although IPV is common, it has not been widely discussed in popular media until recent years when high-profile cases of abuse have come to light. In 2016, a celebrity accusation of domestic violence led to thousands of comments on social media, with outsiders weighing in about who was at fault and what should be done. This study involved a content analysis of 400 of these comments, with the intent of better understanding typical types of social media reactions to domestic violence accusations. Key themes included judgment and blame, with around 37% of commenters blaming the supposed victim in this case, while only 9% blamed the alleged perpetrator. The findings show how people comment about domestic violence and illustrate the contentious and often distorted nature of social media interactions. Implications for professionals and researchers are discussed.

Celebrity suicide on Twitter: Activity, content and network analysis related to the death of Swedish DJ Tim Bergling alias Avicii

BackgroundMedia recommendations for suicide reporting are recommended to prevent imitative suicide but little is known about social media reactions to different revelations about celebrity suicide. MethodsUsing the Twitter Application Programming Interface (API), we recorded public tweets mentioning Avicii from the day when his death was reported (N = 2,865,292). We compared that data with a dataset of random tweets. Furthermore, we recorded tweets including suicide in 124 languages before Avicii‘s death (N = 5,939,107). We processed English tweets mentioning Avicii with the Linguistic Inquiry and Word Count (LIWC) to quantify the frequency of affects and related linguistic signals. We also processed the text of tweets to detect tweets mentioning the suicide method, and we retrieved the list of followers of users who tweeted about the method. We constructed reply networks from the dataset, analysing three networks corresponding to the major news events about Avicii‘s death. ResultsAvicii's suicide sparked immediate strong interest with both positive (χ² = 781.06, p < 10−6) and negative emotional expressions (χ² = 1518.5, p < 10−6) in comparison to baseline levels. Subsequent revelations were associated with smaller peaks with mainly negative emotional content after Avicii's death was revealed as a suicide (χ² = 33.2, p < 10−6 and after news about the suicide method (χ² = 274.93, p < 10−6). Tweeting about the suicide method was infrequent, but twitter users who covered the method had more followers that users who did not (D = 0.1675, p < 10−6; t = 19.87, p < 10−6), and a noteworthy number of users had considerable exposure to the suicide method. LimitationsThis was a descriptive analysis. ConclusionsTwitter users showed strong interest in news about Avicii's death and Avicii's suicide, but less so in the suicide method, and showed distinct tweeting behaviours based on the different revelations.

Challenging social norms: discourse analysis of a research project aiming to use financial incentives to change breastfeeding behaviours

BackgroundThe UK has one of the lowest breastfeeding rates in the world. The NOurishing Start for Health (NOSH) cluster-randomised trial was a trial of a financial incentive scheme that aimed to increase breastfeeding in UK areas where breastfeeding was not the norm (South Yorkshire, Derbyshire, and Nottinghamshire). The announcement of the initial field test of the Vouchers for Breastfeeding scheme generated a substantial amount of (mainly negative) media and social media coverage. Given the media interest and scrutiny in public health research and action (especially where financial incentives are concerned), we aimed to understand negative responses, and the underlying values they represent, to inform future public health research into financial incentives. MethodsA researcher (DU) external to the project and the research area led a discourse analysis of the research project archive, drawing upon more than 500 documents that included team briefs, scholarly articles, publicity material, media reports, and online responses. The purpose of the analysis was to identify where conflicting values were apparent, particularly those at critical transition points in the project, which facilitated further content and visual analysis of relevant documents. FindingsThe analysis exposed fundamental, opposing, and apparently intractable views on the use of financial incentives to increase breastfeeding in the UK. These conflicting positions were apparent from the early stages of the research project and recurred at critical points during the development and delivery of the scheme. In contrast to local stakeholder views, media and social media commentators tended to marginalise the research question and focus instead on discussing why offering incentives for breastfeeding should not be national policy. The analysis also revealed how the project researchers used extensive stakeholder consultation, deployed sensitive language in all public engagements, and adapted well-established visual representations of financial incentives, to navigate through the inherent controversy. InterpretationProjects that challenge societal behavioural norms should anticipate strong and sometimes hostile reactions when planning and progressing their research. Also, researchers should not assume that media and social media reactions represent the considered views of stakeholders directly affected by the research, which in this case were mothers (and their health-care providers) in the areas where the scheme was being trialled. FundingMedical Research Council (MR/J000434/1) via the National Prevention Research Initiative Phase 4 awards.

Leveraging Twitter to gauge evacuation compliance: Spatiotemporal analysis of Hurricane Matthew.

Hurricane Matthew was the deadliest Atlantic storm since Katrina in 2005 and prompted one of the largest recent hurricane evacuations along the Southeastern coast of the United States. The storm and its projected landfall triggered a massive social media reaction. Using Twitter data, this paper examines the spatiotemporal variability in social media response and develops a novel approach to leverage geotagged tweets to assess the evacuation responses of residents. The approach involves the retrieval of tweets from the Twitter Stream, the creation and filtering of different datasets, and the statistical and spatial processing and treatment to extract, plot and map the results. As expected, peak Twitter response was reached during the pre-impact and preparedness phase, and decreased abruptly after the passage of the storm. A comparison between two time periods—pre-evacuation (October 2th-4th) and post-evacuation (October 7th-9th)—indicates that 54% of Twitter users moved away from the coast to a safer location, with observed differences by state on the timing of the evacuation. A specific sub-state analysis of South Carolina illustrated overall compliance with evacuation orders and detailed information on the timing of departure from the coast as well as the destination location. These findings advance the use of big data and citizen-as-sensor approaches for public safety issues, providing an effective and near real-time alternative for measuring compliance with evacuation orders.

The Eurosceptic Europeanization of public spheres: print and social media reactions to the 2014 European Parliament elections

The present study tests the theoretical claim that Eurosceptics contribute to the Europeanization of national public spheres. Although advocating a renationalization of European politics, Eurosceptic parties can engender public media debates of transnational or European relevance. Through a comparative research design of two national cases (Sweden and Denmark), we examine the public discourse on the day following the 2014 European Parliament elections across three media: print, Twitter, and Facebook. Separating the discussions of Eurosceptic issues and actors from other topics of the election coverage, we find that the discourses about Euroscepticism exhibit a higher degree of Europeanization in four of the six media analyzed. Moreover, while we detect significant differences in valence between the Swedish and Danish press when reporting about the Eurosceptics, such national variation is much less pronounced on the social networking sites. The findings suggest, firstly, that Eurosceptics’ contestation of the EU may have the unintended effect of giving national media debates a stronger European dimension. Secondly, the study warrants moderate optimism for the Europeanization potential of social media vis-a-vis traditional media structures: Print media was more Europeanized in scope, whereas social media publics were more aligned in their sentiment toward Euroscepticism.

Political relevance in the eye of the beholder: Determining the substantiveness of TV shows and political debates with Twitter data

Addressing the call to move beyond a simple genre classification of TV shows as either substantive (hard) news or non-substantive (soft) infotainment, we propose using social media reactions to determine a program’s political relevance. Such an approach provides information that goes beyond genre or content characteristics and reflects what really reaches an audience. Analyzing tweets about two Dutch talk shows and four U.S. primary debates, we show that audience responses to television programs differ considerably regarding their political relevance. Thereby, we demonstrate how examining online audience reactions can be employed as a sophisticated and valid way to assess the political relevance of TV programs.

DESIGN, ANALYSIS AND IMPLEMENTATION OF GEOLOCATION BASED EMOTION DETECTION TECHNIQUE OVER TWITTER DATA

It has been a topic of utmost importance to researchers that emotions of public has a direct impact on various social science problems such as politics, online business and so on. With emotion analysis, we can bring sensitivity to analytics and stay attuned to the feelings of customers during chat sessions, track social media reactions to a press releases, or gauge the public outlook on financial news. In order to meet these need we create a system for analyzing moods of tweets on any topic trending on twitter.com. We collected 1. 3 × 10^3 emotional tweets, and then these were annotated for emotion, geographic location. Bayes classifier has been used for analysis.

TGSum: Build Tweet Guided Multi-Document Summarization Dataset

The development of summarization research has been significantly hampered by the costly acquisition of reference summaries. This paper proposes an effective way to automatically collect large scales of news-related multi-document summaries with reference to social media's reactions. We utilize two types of social labels in tweets, i.e., hashtags and hyper-links. Hashtags are used to cluster documents into different topic sets. Also, a tweet with a hyper-link often highlights certain key points of the corresponding document. We synthesize a linked document cluster to form a reference summary which can cover most key points. To this aim, we adopt the ROUGE metrics to measure the coverage ratio, and develop an Integer Linear Programming solution to discover the sentence set reaching the upper bound of ROUGE. Since we allow summary sentences to be selected from both documents and high-quality tweets, the generated reference summaries could be abstractive. Both informativeness and readability of the collected summaries are verified by manual judgment. In addition, we train a Support Vector Regression summarizer on DUC generic multi-document summarization benchmarks. With the collected data as extra training resource, the performance of the summarizer improves a lot on all the test sets. We release this dataset for further research.

Beyond positive or negative: Qualitative sentiment analysis of social media reactions to unexpected stressful events

Sentiment analysis techniques are increasingly used to grasp reactions from social media users to unexpected and potentially stressful social events. This paper argues that, alongside assessments of the affective valence of social media content as negative or positive, there is a need for a deeper understanding of the context in which reactions are expressed and the specific functions that users' emotional states may reflect. To demonstrate this, we present a qualitative analysis of affective expressions on Twitter collected in Germany during the 2011 EHEC food contamination incident based on a coding scheme developed from Skinner et al.'s (2003) coping classification framework. Affective expressions of coping were found to be diverse not only in terms of valence but also in the adaptive functions they served: beyond the positive or negative tone, some people perceived the outbreak as a threat while others as a challenge to cope with. We discuss how this qualitative sentiment analysis can allow a better understanding of the way the overall situation is perceived – threat or challenge – and the resources that individuals experience having to cope with emerging demands.

Global Handwashing Day 2012: a qualitative content analysis of Chinese social media reaction to a health promotion event.

Global Handwashing Day (GHD) is a handwashing promotion campaign organized by the Global Public-Private Partnership of Handwashing with Soap. In China, it has been promoted by the Chinese public health authorities, international organizations and multinational corporations through various channels including social media such as Sina Weibo, the leading Chinese microblogging site similar to Twitter. The objective of this study is to qualitatively assess Chinese social media users' reactions to a health promotion campaign using Global Handwashing Day (GHD) 2012 as an example. We conducted a qualitative content analysis of 552 Weibo posts generated on GHD 2012 by Weibo users with 1000 or more followers with the Chinese keyword for "handwashing." We categorized the Weibo posts into groups by keywords that frequently appeared in the data set. These groups were either exact reposts of an original post, or they conveyed similar information. We observed the interconnections between traditional media and social media in handwashing promotion. Social media were found to serve as amplifiers of contents provided by traditional media. We observed the contextualization of global hygiene messages in a unique national social media market in China. Our study showed that social media and traditional media are two interconnected arms of the GHD campaign in China. Our analysis demonstrated that public health campaigns in China can be evaluated using social media data. The themes and topics identified in this study will help public health practitioners evaluate future social media handwashing promotion campaigns.