Twitter Activity Research Articles

Towards a typology of humorous wartime tweets

The idea of this research was born on 26 May 2022. The following day, we saw Elon Musk’s tweet from 26 May 2022: ‘Politics is a sadness generator’. We accepted the challenge to refute the statement and to prove that there is much space for humour in the political discourse. The study focuses on humorous tweets produced in the period of the first 100 days of the 2022 Russian invasion of Ukraine and the criteria according to which they may be classified for further analysis. The literature overview proves that humour has been extensively approached by different researchers from a multidisciplinary perspective; in particular, numerous attempts were made to classify humour and its manifestations. In this research, we approached the Twitter activity of Ukrainian politicians as fragments of political discourse. In particular, we extracted humorous tweets and organised a sample that underwent further categorisation and interpretation with reference to existing typologies and theories of humour. The study discusses the roles the politicians assume while producing and spreading humour on Twitter, features the key subject fields and objects of ridicule in the wartime tweets, gives an insight into the communicative value of such tweets and suggests potential readership classes. Finally, the study seeks to prove the flexibility and adaptability of humour styles to the socio-political context and wartime communication that project public aggressiveness, self-relief and self-enhancement

Commentary—Much ado About Something Else. Donald Trump, the US Stock Market, and the Public Interest Ethics of Social Media Communication

We analyze Donald J. Trump’s Twitter activity over the last months of the 2016 presidential campaign, his period as President Elect, and his Presidential term until Fall 2019, shortly before the outbreak of the pandemic. Trump weaponized social networks as a communication tool to build influence on the financial market and the public opinion. We relate Trump’s communication on Twitter to the dynamics of the NASDAQ100 trend over the whole period of study as well as two subperiods, pre-presidential versus presidential. We find that Trump’s hyperactivity on Twitter is followed by a negative market trend, and that tweets covering politically, and economically sensitive topics seem to negatively impact the market, except for real economy-related tweets. Some topics positively received by the market in the pre-presidential phase (e.g., China) become anticipators of negative trading days during the presidential one. We also consider the emotional tone of Trump’s tweets and find an unexpected reversal of the communicative valence of the tweets as to their expected impact on the stock market. Positive sentiment tweets seem to be followed by negative market performance and, maybe more surprisingly, vice versa. It seems that, during the period of observation, the market has learnt to interpret the emotional tone of Trump’s tweets as instrumental to Trump’s political strategy. In particular, the market seems to have realized that negative sentiment in Trump’s communication was entirely functional to political consensus building and not meant to convey market-relevant information. This is at odds with the idea that presidential communication should reflect the public interest, and especially so when it has major implications for the economy. Trump’s use of social media during both his presidential campaign and term questions the principle that institutional responsibility in the digital realm implies treating the infosphere as a commons. We discuss the implications for the functioning of the stock market and the emerging public interest ethical issues related to the breakdown of such principle.

Slow, slow, quick, quick, slow: five altmetric sources observed over a decade show evolving trends, by research age, attention source maturity and open access status.

The study of temporal trends in altmetrics is under-developed, and this multi-year observation study addresses some of the deficits in our understanding of altmetric behaviour over time. The attention surrounding research outputs, as partially captured by altmetrics, or alternative metrics, constitutes many varied forms of data. Over the years 2008-2013, a set of 7739 papers were sampled on six occasions. Five altmetric data sources were recorded (Twitter, Mendeley, News, Blogs and Policy) and analysed for temporal trends, with particular attention being paid to their Open Access status and discipline. Twitter attention both starts and ends quickly. Mendeley readers accumulate quickly, and continue to grow over the following years. News and blog attention is quick to start, although news attention persists over a longer timeframe. Citations in policy documents are slow to start, and are observed to be growing over a decade after publication. Over time, growth in Twitter activity is confirmed, alongside an apparent decline in blogging attention. Mendeley usage is observed to grow, but shows signs of recent decline. Policy attention is identified as the slowest form of impact studied by altmetrics, and one that strongly favours the Humanities and Social Sciences. The Open Access Altmetrics Advantage is seen to emerge and evolve over time, with each attention source showing different trends. The existence of late-emergent attention in all attention sources is confirmed.

Orienting toward the otherwise in the Twitterverse: Activating pedagogical commitments with pedagogists and Twitter

This article asks how social media platform engagement, on Twitter in particular, collides with thinking and experimenting with the educational practice of a pedagogist. Beginning with tracing the role of the pedagogist as an emerging figure in early childhood education within the Canadian context, we turn to thinking #BecomingPedagogist, the hashtag used on Twitter by those undertaking work toward responding to and inventing the digital practices of a pedagogist. We situate the labor of a pedagogist on Twitter amid public pedagogies and then follow some contemporary threads of Twitter activism. Then, we offer two “problems” for pedagogists on Twitter: (1) settler moves to innocence through utilizing “beauty” as a primary frame for engaging with tweets from Indigenous people; (2) resisting the pull of individualizing, productivity-oriented neoliberal logics on Twitter. We conclude by offering questions we hope pedagogists will consider and continue to grapple with throughout the collective project of thinking pedagogists’ online practices.

Managerial Strategic Earnings Disclosure via Social Media: Evidence from 18 Million Corporate Tweets

Using a broad sample of earnings announcement tweets (EATs) constructed from 18 million corporate tweets, we document that there exists a substitute relationship between EATs and management earnings forecasts (MEFs). EATs reduce the use and improve the accuracy of MEFs and analysts’ forecast for contemporaneous and subsequent quarters. Such improvement is more pronounced in the presence of negative earnings news. Furthermore, firms with EATs are associated with higher profitability, better information environment, and lower liquidity. Using textual analysis, we show that firms with positive tone of EATs are more likely to have positive earnings surprise. Overall, our findings provide novel evidence on the significant association between corporate Twitter activities and managers’ strategic disclosure as well as firms’ information environment and future performance.

#MahsaAmini: Iranian Twitter Activism in Times of Computational Propaganda

ABSTRACT This paper discusses 1) how #MahsaAmini has become a significant hybrid movement in Iran and 2) how it is taking Twitter activism into the post-fake news era. I will begin by reviewing the existing literature on Twitter and democracy. Then, I will discuss the roots of the #MahsaAmini, which make it a hybrid movement. Further, I will show how Iranians have circumvented the regime’s fake news campaigns and cyber army. This paper argues that while non-democratic regimes have developed more complex methods of suppressing digital protests, these efforts are ineffective in large-scale protests.

Twitter Interactions in the Era of the Virtual Academic Conference: A Comparison Between Years

Abstract The goal of this study is to assess variations in interactions over social media at academic conferences when held onsite versus online. Here, Twitter activities from different years of the Annual Meeting of the Association for Information Science and Technology (ASIS&T AM) are analyzed and reported. Data elements of individual tweets were examined using both primary- and second-level analyses, showing overall participation levels and the number of actions across different variables. The activity level and relative impact on the overall results of users who appeared in both years emerged as a key finding. Twitter activities during both the 2018 (Vancouver) and 2020 (online) ASIS&T AM were collected and compared.

Social Services and Twitter: Analysis of Socio-Political Discourse in Spain from 2015 to 2019

The fundamental role of social networks in all areas of our lives and of social and political interactions is also very important in this new digital environment. The study focused on the analysis of tweets related to social-service issues published on Twitter during the different electoral campaigns in Spain from 2015 to 2019. The sample is 6728 tweets generated between 2015 and 2019 on the topic “social services” for quantitative analysis. In this analysis, we use the Gephi tool to observe how these messages flow on Twitter. The aim was to understand the socio-political discourse of different actors on social services in order to identify priority topics and networks for active Twitter profiles. The results show that users use Twitter for informal communication during the election period, focusing on messages, condemnation and positive evaluation to increase their visibility and influence.

Fanbois and Fanbots: Tesla’s Entrepreneurial Narratives and Corporate Computational Propaganda on Social Media

This paper reports the discovery of a series of computational social media accounts (Fanbots) on Twitter that may have played a critical role in sustaining the entrepreneurial narratives of Tesla, the electric-vehicle maker. From 2010 to 2020—a period of trial, error, and eventual success for Tesla—these computational agents generated pro-firm tweets (Corporate Computational Propaganda, CCP), accounting for more than 10% of the total Twitter activity that included the cashtag, $TSLA, and 23% of activity that included the hashtag, #TSLA. Though similar to programmed social media content in the political sphere, the activities of these accounts predate the existence of political computational propaganda associated with foreign support for, for instance, Brexit in the United Kingdom (2016) and Donald Trump in the United States (2016). The paper (a) characterizes the extent of Fanbot content in two large Tesla tweet corpora, (b) identifies possible motivations for the creation of these accounts in relation to the firm’s entrepreneurial narratives, and (c) explores possible mechanisms by which the Fanbots might have acted. Although we are unable to directly observe the source or stated purpose of these accounts, based upon the timing of Fanbot creation and other indirect indicators, we infer that these accounts and the social media activity they generated were intended to influence social perception of Tesla. The conclusion assesses the generalizability of a Fanbot-based strategy, highlighting contextual limitations, while also pointing to ways that firms may already be using CCP to manage social approval in emerging-industry contexts.

Rage in the Machine: Activation of Racist Content in Social Media

ABSTRACTRacism in social media is ubiquitous, persisting online in ways unique to the internet while also reverberating from the world offline. When will racist frames activate in social media networks? This article argues that social media users engage with racist content when they perceive a threat to the in-group status, selecting frames that serve as markers to separate the in-group identity from the out-group identity. Racialized frames serve as these markers, and the perceived threats to the in-group status make racist content cognitively congruent. Evidence of this behavior is provided by examining Twitter activity during the indígena protests in Ecuador in October 2019. A novel, multistep machine-learning process detects racist tweets, and an interrupted time series analysis shows how events that can be perceived as threats to the in-group activate racist content in some social media communities.

Relationship between Twitter activity and stock performance: evidence from Turkish airline industry

PurposeThe purpose of this paper is to analyze the correlation between the Twitter activity of two airline companies and their stock performance at the Istanbul Stock Exchange (BIST).Design/methodology/approachOverall, 113,018 tweets were divided into 34,152 semantic and 78,866 share tweets. Semantic tweets are tweets mentioning company’s products or services and were labeled manually and with deep learning models. Share tweets were divided into 13,618 relevant and 65,248 irrelevant tweets.FindingsA positive correlation was found between share tweets and stock performance. Semantic tweets did not display a correlation with stock performance. Relevant share tweets displayed as a strong correlation as all share tweets for one company. Also, the manual labeling of 8,000 tweets led to the discovery of many insights related to service provision in the airway industry, management of digital support channels, management of reputation on social media and using Twitter as a customer support platform.Practical implicationsRelevant share tweets comprise only 20% of all share tweets for one company and show the same level of correlation with stock performance. This means that the efficiency of business intelligence solutions created to monitor Twitter activity can be improved five times by saving computational power, network bandwidth and data storage.Originality/valuePrevious research has analyzed all Twitter activity taken together. By dividing tweets into semantic and share tweets, this paper illustrates that it is, in fact, share tweets that are correlated with stock performance and not semantic tweets.

To Tweet or not to Tweet? The Determinants of Tweeting Activity in Initial Coin Offerings

AbstractOur research explores the causes of Twitter activity in highly technological start‐ups that finance their activities via initial coin offerings (ICOs). By relying on weekly data of 297 ICOs for the period 2015–2020 (35,459 observations), we examine how major exogenous events affect the number of tweets issued by the start‐up. Then, we explore how the community of followers reacts to the tweets. We discover that events external to firms reduce ICOs’ tweeting activity. Moreover, our evidence indicates that the followers’ reaction is positively related to the tweets issued by the firm and negatively related to major events unrelated to the firm. Interestingly, followers’ reaction has an inverted U‐shaped relation with the firm's Twitter volume, suggesting that excessive Twitter activity can harm the further dissemination of tweets. Our results, robust to alternative estimation techniques, emphasize the important role of Twitter as an information disseminator, legitimizer, and endorser for highly opaque firms.

A two-year follow-up: Twitter activity regarding misinformation about spinal manipulation, chiropractic care and boosting immunity during the COVID-19 pandemic

BackgroundSpinal manipulative therapy (SMT) is offered by many health professions, most often by chiropractors. While SMT can be effective for some musculoskeletal disorders, there is no evidence that SMT improves human immunity in a clinically meaningful way. Despite this, we showed previously that Twitter misinformation about chiropractic/SMT improving immunity increased sharply at the start of the COVID-19 pandemic. Here, we perform a two-year follow-up.MethodsWe previously employed specialized software (i.e. Talkwalker) to search the entirety of Twitter activity in the months before and after the COVID-19 pandemic was declared (March 11, 2020). In this paper, we conducted follow-up searches over two successive 12 month periods using terms related to SMT, immunity and chiropractic. The resulting tweets were then coded into those promoting/refuting a relation between SMT and immunity (tone) and messaging about chiropractic/interventions (content). Further analyses were performed to subcategorize tweet content, tally likes, retweets and followers, and evaluate refuting tweets and the country of origin. Finally, we created a chronology of Twitter activity superimposed with dates of promoting or refuting activities undertaken by chiropractic organizations.ResultsOver the 27 month study period, Twitter activity peaked on March 31, 2020 then declined continuously. As in our first paper, our follow-up data showed that (1) the ratio of refuting/promoting tweets remained constant and (2) tweets that refuted a relationship between SMT and immunity were substantially more liked, retweeted and followed than those promoting. We also observed that promoting tweets suggesting that SMT improves immunity decreased more rapidly. Overwhelmingly, promoting tweets originated in the USA while refuting tweets originated in Canada, Europe and Australia. The timing of the decline in peak Twitter activity, together with a parallel decline in tweets claiming that SMT improves immunity, was coincident with initiatives by chiropractic organizations and regulators targeting misinformation.ConclusionOverwhelmingly, Twitter activity during the COVID-19 pandemic focussed on refuting a relation between chiropractic/SMT and immunity. A decline in Twitter activity promoting a relation between SMT and immunity was observed to coincide with initiatives from chiropractic organizations and regulators to refute these claims. The majority of misinformation about this topic is generated in the United States.

#OrthoTwitter: Relationship Between Author Twitter Utilization and Academic Impact in Orthopaedic Surgery.

Background #OrthoTwitter has evolved to disseminate findings and engage the public. However, the academic impact of Twitter utilization in orthopaedic surgery is unknown. Questions/purposes The purpose of the study was to evaluate relationships between the author and manuscript Twitter activity and citations. Methods Manuscripts in 17 orthopaedic journals from 2018 were identified. Citations, online mentions, impact factors, and subspecialties were obtained. H-index and Twitter account details for authors were obtained for a subset of manuscripts. Relationships between Twitter activity and citations were evaluated. Results 2,473/4,224 (58.5%) manuscripts were mentioned on Twitter (n=29,958 mentions), with Twitter manuscripts cited more frequently (median 10 vs. 7, p<0.0001). Twitter mentions, impact factors, non-open-access status, and subspecialties were associated with citation counts. Articles mentioned in 10, 100, and 1,000 Tweets were observed to have a 1.1-fold, 1.7-fold, and 245-fold increase in citations. In author-level analyses, 156 (20.0%) first and 216 (27.7%) senior authors had Twitter accounts. Citation count was associated with increasing senior author H-index (β est=0.13, p<0.05), Twitter mentions (β est=0.0043, p<0.0001), impact factors (β est=0.13, p<0.0001), and having a first (β est=0.20, p<0.05) or senior author (β est=0.17, p<0.05) on Twitter. Articles published in arthroplasty (β est=0.49, p<0.05), general interest (β est=0.55, p<0.01), sports (β est=0.63, p<0.01), and non-open access journals (β est=0.41, p<0.001) were cited more. H-index correlated with followers for first (rho=0.31, p<0.0001) and senior authors (rho=0.44, p<0.0001). Conclusion Author Twitter utilization is independently associated with manuscript citations. Authors should be aware of the potential association between social media utilization and traditional academic impact. Understanding the relationship between social media utilization and academic impact is necessary to effectively disseminate research.

Correlating Twitter Use with Disaster Resilience at Two Spatial Scales: A Case Study of Hurricane Sandy

ABSTRACT Disaster resilience describes the ability of a community to bounce back from disaster impacts by resilience building activities. Social media provides an innovative way to observe human attitudes and responses, especially during disasters. However, most previous social media and disasters studies were conducted at a coarse spatial scale such as by county. This study analyzes Twitter activities during Hurricane Sandy in 2012, at the county and the zip code area levels in the five affected states. The study examines two questions: (1) will the relationships between disparities in social media use and disparities in disaster resilience found at the county level in previous studies still hold at the zip code area level? And (2) what new information or patterns can be revealed with the zip code area level analysis? Results show that correlations between Twitter use indices and social-environmental variables representing community resilience found at the county level in previous studies still hold, but they are weaker at the zip code area level. The study also shows that zip code areas that have major transportation hubs and commercial activities or low night-time population are major factors affecting Twitter use indices and hence the correlations. Future research should consider adding data on land use types and population dynamics to help improve social media use for disaster resilience analysis. Furthermore, employing a multiscale analysis approach can reduce uncertainties involved in analysis and obtain a more thorough understanding of the relationships between Twitter use and geographical and socioeconomic characteristics of the affected communities.

Do Social Media Influence CEOs’ Strategic Decisions? CEOs’ Twitter Activity and Subsequent M&amp;amp;As

Do Social Media Influence CEOs’ Strategic Decisions? CEOs’ Twitter Activity and Subsequent M&amp;amp;As

Twitter trends in #Parasitology determined by text mining and topic modelling

This study investigated the emergence and use of Twitter, as of July 2023 being rebranded as X, as the main forum for social media communication in parasitology. A dataset of tweets was constructed using a keyword search of Twitter with the search terms ‘malaria’, ‘Plasmodium’, ‘Leishmania’, ‘Trypanosoma’, ‘Toxoplasma’ and ‘Schistosoma’ for the period from 2011 to 2020. Exploratory data analyses of tweet content were conducted, including language, usernames and hashtags. To identify parasitology topics of discussion, keywords and phrases were extracted using KeyBert and biterm topic modelling. The sentiment of tweets was analysed using VADER. The results show that the number of tweets including the keywords increased from 2011 (for malaria) and 2013 (for the others) to 2020, with the highest number of tweets being recorded in 2020. The maximum number of yearly tweets for Plasmodium, Leishmania, Toxoplasma, Trypanosoma and Schistosoma was recorded in 2020 (2804, 2161, 1570, 680 and 360 tweets, respectively). English was the most commonly used language for tweeting, although the percentage varied across the searches. In tweets mentioning Leishmania, only ∼37% were in English, with Spanish being more common. Across all the searches, Portuguese was another common language found. Popular tweets on Toxoplasma contained keywords relating to mental health including depression, anxiety and schizophrenia. The Trypanosoma tweets referenced drugs (benznidazole, nifurtimox) and vectors (bugs, triatomines, tsetse), while the Schistosoma tweets referenced areas of biology including pathology, eggs and snails. A wide variety of individuals and organisations were shown to be associated with Twitter activity. Many journals in the parasitology arena regularly tweet about publications from their journal, and professional societies promote activity and events that are important to them. These represent examples of trusted sources of information, often by experts in their fields. Social media activity of influencers, however, who have large numbers of followers, might have little or no training in science. The existence of such tweeters does raise cause for concern to parasitology, as one may start to question the quality of information being disseminated.

Via Twitter ins Amt: Karl Lauterbach, die Corona-Pandemie und das Bundesgesundheitsministerium

This article argues that Karl Lauterbach accomplished the office of federal secretary of health mainly due to his Twitter activities and the concomitant exposure in political TV talk shows . Lauterbach had little intraparty support after his failed bid for SPD leadership . He did not hold a senior office within his parliamentary group or within the health policy community . The Land party of North Rhine-Westphalia had placed him on a hopeless position of the Land list for the federal elections . Finally, he played a minor role in the coalition negotiations and did not lead the talks on health policy for his party . With a view to all known informal rules for the selection of government ministers, he was certainly not part of the pool of likely candidates . The detailed quantitative analyses of Lauterbach’s Twit ter and media activities show that it was most likely this self-generated public visibility which explains his appointment .

Agriculture and International Organization in Indonesia: The Twitter Analysis of FAO Indonesia

World agriculture confronts diverse challenges, including climate change, food security, soil degradation, water scarcity, biodiversity loss, and rural poverty. Addressing these interlinked issues necessitates a collaborative, multidisciplinary approach involving governments, farmers, scientists, civil society, and international organizations. Understanding the role of the Food and Agriculture Organization (FAO) in Indonesia is pivotal. Analyzing the Twitter activities of FAO Indonesia (@FAOIndonesia) provides insights into their efforts related to Indonesian agriculture. This study employs qualitative content analysis, utilizing NVivo software to assess sentiment, dominant themes, and specific topics within @FAOIndonesia’s Twitter account. The findings reveal a prevalence of negative sentiment over positive sentiment in FAO Indonesia’s Twitter discourse. Furthermore, the dominance of “https” in word frequency indicates that FAO Indonesia primarily shares links to access detailed information on agriculture issues, rather than providing comprehensive information directly on Twitter. This research yields significant insights into agriculture issues in Indonesia, valuable for policymakers and international organizations operating in the country, highlighting the need for more direct communication and information dissemination to address the multifaceted challenges facing agriculture.

Police Use of Twitter During a Sporting Mega-Event

Abstract There exists a range of sporting mega-event security case studies from respective Olympic Games, Commonwealth Games, International Association Football Federation (FIFA) World Cup, and Union of European Football Associations (UEFA) Championships. This literature tends to focus on outlining the policing and physical security arrangements at respective Games and the social consequences of these. However, no studies have examined police use of social media at a mega-event. This article addresses this gap by analysing the Twitter activities of social media accounts from police forces and units within Glasgow and London during the Euro 2020 Finals. The article makes an empirical contribution to the mega-events and policing literature by identifying that the police used Twitter in five strategic ways: security spectacle, demonstration of effective partnership working, responsibilization of citizens, public feedback and reporting, and real-time crowd management. Such findings have important implications for the use of social media by police practitioners at future mega-events and for football policing.