Twitter Activity Research Articles

Friendship Paradox Redux: Your Friends Are More Interesting Than You

Feld's friendship paradox states that "your friends have more friends than you, on average." This paradox arises because extremely popular people, despite being rare, are overrepresented when averaging over friends. Using a sample of the Twitter firehose, we confirm that the friendship paradox holds for >98% of Twitter users. Because of the directed nature of the follower graph on Twitter, we are further able to confirm more detailed forms of the friendship paradox: everyone you follow or who follows you has more friends and followers than you. This is likely caused by a correlation we demonstrate between Twitter activity, number of friends, and number of followers. In addition, we discover two new paradoxes: the virality paradox that states your friends receive more viral content than you, on average, and the activity paradox, which states your friends are more active than you, on average." The latter paradox is important in regulating online communication.It may result in users having difficulty maintaining optimal incoming information rates, because following additional users causes the volume of incoming tweets to increase super-linearly.While users may compensate for increased information flow by increasing their own activity, users become information overloaded when they receive more information than they are able or willing to process. We compare the average size of cascades that are sent and received by overloaded and underloaded users. And we show that overloaded users post and receive larger cascades and they are poor detector of small cascades.

It Is Not Only About Grievances: Emotional Dynamics in Social Media During the Brazilian Protests

In the summer of 2013, Brazil experienced a period of conflict triggered by a series of protests. While the popular press covered the events, little empirical work has investigated how first-hand reporting of the protests occurred and evolved over social media and how such exposure in turn impacted the demonstrations themselves. In this study we examine over 42 million tweets shared during the three months of conflict in order to uncover patterns in online and offline protest-related activity as well as to explore relationships between language-use in tweets and the emotions and underlying motivations of protesters. Our findings show that peaks in Twitter activity coincide with days in which heavy protesting took place, that the words in tweets reflect emotional characteristics of protest-related events, and less expectedly, that these emotions convey both positive as well as negative sentiment.

Why You Are More Engaged: Factors Influencing Twitter Engagement in Occupy Wall Street

Twitter has been used for engaging with audiences online in several popular political movements. In this paper we explore factors that influence the engagement of Twitter users during the recent Occupy Wall Street movement, where engagement is measured by retweets and hashtag usage related to the movement. Through analyzing Twitter activities of more than 18,000 users, we found that users’ general activity level, geographic location, topic interests and interpersonal interactions before the movement all had measurable effects on users’ engagement level during the movement.

Predicting User Engagement on Twitter with Real-World Events

People invest time, attention, and emotion while engaging in various activities in the real-world, for either purposes of awareness or participation. Social media platforms such as Twitter offer tremendous opportunities for people to become engaged in such real-world events through information sharing and communicating about these events. However, little is understood about the factors that affect people's Twitter engagement in such real-world events. In this paper, we address this question by first operationalizing a person's Twitter engagement in real-world events such as posting, retweeting, or replying to tweets about such events. Next, we construct statistical models that examine multiple predictive factors associated with four different perspectives of users' Twitter engagement, and quantify their potential influence on predicting the (i) presence; and (ii) degree — of the user's engagement with 643 real-world events. We also consider the effect of these factors with respect to a finer granularization of the different categories of events. We find that the measures of people's prior Twitter activities, topical interests, geolocation, and social network structures are all variously correlated to their engagement with real-world events.

The effect of intra-urban mobility flows on the spatial heterogeneity of social media activity: investigating the response to rainfall events

ABSTRACT Although it is acknowledged that urban inequalities can lead to biases in the production of social media data, there is a lack of studies which make an assessment of the effects of intra-urban movements in real-world urban analytics applications, based on social media. This study investigates the spatial heterogeneity of social media with regard to the regular intra-urban movements of residents by means of a case study of rainfall-related Twitter activity in São Paulo, Brazil. We apply a spatial autoregressive model that uses population and income as covariates and intra-urban mobility flows as spatial weights to explain the spatial distribution of the social response to rainfall events in Twitter vis-à-vis rainfall radar data. Results show high spatial heterogeneity in the response of social media to rainfall events, which is linked to intra-urban inequalities. Our model performance () provides evidence that urban mobility flows and socio-economic indicators are significant factors to explain the spatial heterogeneity of thematic spatiotemporal patterns extracted from social media. Therefore, urban analytics research and practice should consider not only the influence of socio-economic profile of neighborhoods but also the spatial interaction introduced by intra-urban mobility flows to account for spatial heterogeneity when using social media data.

Taking It All In? Visual Attention in Microblog Consumption

Microblogging environments such as Twitter present a modality for interacting with information characterized by exposure to information “streams”. In this work, we examine what information in that stream is attended to, and how that attention corresponds to other aspects of microblog consumption and participation. To do this, we measured eye gaze, memory for content, interest ratings, and intended behavior of active Twitter users as they read their tweet steams. Our analyses focus on three sets of alignments: first, whether attention corresponds to other measures of user cognition such as memory (e.g., do people even remember what they attend to?); second, whether attention corresponds to behavior (e.g., are users likely to retweet content that is given the most attention); and third, whether attention corresponds to other attributes of the content and its presentation (e.g., do links attract attention?). We show a positive but imperfect alignment between user attention and other measures of user cognition like memory and interest, and between attention and behaviors like retweeting. To the third alignment, we show that the relationship between attention and attributes of tweets, such as whether it contains a link or is from a friend versus an organization, are complicated and in some cases counterintuitive. We discuss findings in relation to large scale phenomena like information diffusion and also suggest design directions to help maximize user attention in microblog environments

Determining the Presence of Political Parties in Social Circles

We derive the political climate of the social circles of Twitter users using a weakly-supervised approach. By applying random walks over a sub-sample of Twitter's social graph we infer a distribution indicating the presence of eight Flemish political parties in users' social circles in the months before the 2014 elections. The graph structure is induced through a combination of connection and retweet features and combines information of over a million tweets and 14 million follower connections. We solely exploit the social graph structure and do not rely on tweet content. For validation we compare the affiliation of politically active Twitter users with the most-influential party in their network. On a validation set of around 700 politically active individuals we achieve F_1 scores of 0.85 and greater. We asked the Twitter community to evaluate our classification performance. More than half of the 2258 users who responded reported a score higher than 60 out of 100.

Perception Differences between the Depressed and Non-Depressed Users in Twitter

One's state of mind will influence her perception of the world and people within it. In this paper, we explore attitudes and behaviors toward online social media based on whether one is depressed or not. We conducted semi-structured face-to-face interviews with 14 active Twitter users, half of whom were depressed and the other half non-depressed. Our results highlight key differences between the two groups in terms of perception towards online social media and behaviors within such systems. Non-depressed individuals perceived Twitter as an information consuming and sharing tool, while depressed individuals perceived it as a tool for social awareness and emotional interaction. We discuss several design implications for future social networks that could better accommodate users with depression and provide insights towards helping depressed users meet their needs through online social media.

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

Social media have introduced entirely new ways in which CEOs can communicate; however, our understanding of the impacts of social media communication on CEOs and their decisions has remained limited. I argue that CEOs' social media activity increases their confidence, risk-taking, and M&A activity and decreases their organic growth expenditure. I argue that social media activity can be confusing for external stakeholders, resulting in less favorable market reactions to this increased M&A behavior. I test my theory using the M&A activity of a sample of CEOs from S&P1500. I found that CEOs who are active on Twitter engage in 800 million dollars more expensive deals than before they joined. This effect increases by 1 million dollars for every ten extra tweets. For every thousand tweets, investors’ reactions to this increased M&A activity is one percent less positive. I discuss the implications for the literature on M&A and CEO social media communication.

How has the COVID-19 pandemic affected the climate change debate on Twitter?

Climate change and the COVID-19 pandemic share many similarities. However, in the past months, concerns have increased about the fact the health emergency has put on hold during the pandemic many climate adaptation and mitigation policies. We focus our attention on understanding the role of the recent health emergency on the transmission of information related to climate change, jointly with other socio-economic variables, social norms, and cultural dimensions. In doing so, we create a unique dataset containing the number of tweets written with specific climate related keywords per country worldwide, as well as country specific socio-economic characteristics, relevant social norms, and cultural variables. We find that socio-economic variables, such as income, education, and other risk-related variables matter in the transmission of information about climate change and Twitter activity. We also find that the COVID-19 pandemic has significantly decreased the overall number of messages written about climate change, postponing the climate debate worldwide; but particularly in some vulnerable countries. This shows that in spite of the existing climate emergency, the current pandemic has had a detrimental effect over the short-term planning of climate policies in countries where climate action is urgent.

Voting and Social Media-Based Political Participation

Does online political involvement reinforce or compensate participatory deficiencies at the polls? Extant survey evidence portrays online participation as a weapon of the strong, wielded by a highly politically involved, white, and affluent subset of the American electorate. Surveys face systematic sampling and measurement errors in the domain of political participation, though. In this study, I revisit this question using individual voter registration records that I integrate with observed Twitter activity. Based on a large sample that reflects Florida’s voting-eligible population, I find that political involvement on Twitter is prevalent across the electorate and extends to those most likely to abstain from voting. Moreover, race and income, which are salient dividing lines in voting, do not structure social media-based political participation. These results challenge reinforcement theory and substantiate social media’s compensatory potential for more inclusive representation. I discuss implications for political representation and future research examining political involvement.

#TrendingNow: Instagram Versus Twitter Activity Among Radiation Oncology Patients and Professionals

PurposeWe aimed to evaluate recent Instagram and Twitter posts to identify the primary disseminators of information related to radiation therapy on social media (health care professionals vs patients), to characterize their influencer status, and to characterize the content of this information. Methods and MaterialsUsing 2 commercial hashtag analytics platforms, 1000 of the most recent eligible posts from each platform were evaluated for content, tone, and engagement, as well as user (poster) characteristics. Inclusion criteria were as follows: unique posts, written in English, relevant to human cancer treatment, and containing 1 of 11 predetermined hashtags (#radiation, #radiotherapy, #radiationtherapy, #radiationoncology, #radonc, #radiationtherapist #radiationtreatment, #medphys, #cyberknife, #radiosurgery, #protontherapy). ResultsUsers of radiation oncology content on Instagram were primarily patients/caregivers (47%), specifically adult patients (94%) with breast cancer (53%). Patient/caregiver content was focused on patient experience (79%), with approximately half specific to radiation therapy (51%), and most patient/caregiver posts demonstrated a positive tone (86%). In contrast, Twitter content was dominated by health care professionals (53%), specifically within radiation oncology (90% of unique users). Health care professional content was focused on colleague education/research dissemination (53%), with a high proportion of posts specific to radiation therapy (95%). ConclusionsGiven the disproportionate number of patients versus radiation oncology professionals active on Instagram versus Twitter, and the lack of radiation therapy-specific content on Instagram, there may be an opportunity to improve patient outreach and education by promoting the presence of radiation oncologists on Instagram.

Shock and awe: Loudness and unpredictability in Twitter messages and crowdfunding campaign success

Although recent evidence has found support for the importance of social media in communicating specific messages between venture founders and their target audience, there remains a relative paucity of research regarding how specific temporal elements of social media activity are related to key venture development outcomes. In this context, the current study draws on the conceptual framework of shock advertising to understand how louder (i.e., an increasing number of tweets) and unpredictable (i.e., tweets at non-standard times) Twitter activity can improve the odds of crowdfunding success. Using a sample of Kickstarter projects between 2009 and 2018 and cross-sectional regressions (ordinary least squares and the logit model), we find that the odds of meeting goals increase 1.24 times with each percentage increase in tweets, relative to tweets in the project-category-year. The odds of success increase further with an increase in the unpredictability and number of project-category-year adjusted tweets. In an era when standing out in the social media is increasingly challenging, our findings have implications for managing social media messages during crowdfunding campaigns.

Prime Ministers on Twitter

The aim of this paper is to analyse Twitter activity of Prime Ministers of Poland and of the Czech Republic, Mateusz Morawiecki and Andrej Babiš respectively, during the 2019 European Parliament election campaign with the special focus on their ways of creating, imposing and reproducing the campaign discourse. It examines especially the person-alization of the election campaign, namely using the election-related activities to promote their image. Also, the im-portance of hashtags as a strategy for building discursive styles is explored and ways of using political pretexts e.g. the Europe Day to introduce election themes are compared. In this context the answer to the following question pre-sents itself as a research challenge: to what extent PMs’ tweets impact the course and the dynamics of the campaign and to what extent it is just dry information, a press commentary?

Influence of the pandemic lockdown on Fridays for Future's hashtag activism.

Social movement organizations (SMOs) increasingly rely on Twitter to create new and viral communication spaces alongside newsworthy protest events and communicate their grievance directly to the public. When the COVID-19 pandemic impeded street protests in spring 2020, SMOs had to adapt their strategies to online-only formats. We analyze the German-language Twitter communication of the climate movement Fridays for Future (FFF) before and during the lockdown to explain how SMOs adapted their strategy under online-only conditions. We collected (re-)tweets containing the hashtag #fridaysforfuture (N = 46,881 tweets, N = 225,562 retweets) and analyzed Twitter activity, use of hashtags, and predominant topics. Results show that although the number of tweets was already steadily declining before, it sharply dropped during the lockdown. Moreover, the use of hashtags changed substantially and tweets focused increasingly on thematic discourses and debates around the legitimacy of FFF, while tweets about protests and calls for mobilization decreased.

Social Construction of Blockchain on Social Media: Framing Public Discourses on Twitter

Blockchain has become a hot topic in technology, finance, regulation, and the wider society in recent years. Along the way, various users and interests have shaped the technology materially and discursively. This paper investigates the debate taking place on Twitter surrounding blockchain technology to understand the nature and development of its online public discourses. We collected and analyzed a Twitter dataset containing a total of 267,512 tweets that reference blockchain by 105,734 unique users. We conducted a mixed method research study involving qualitative and quantitative approaches. The results indicate that the majority of the retweeted posts are educational and promotional in nature, while the lowest numbers of frames are critical or skeptical of the new technology. The most active users seem to be largely involved in promoting the technology including some that are human created bots. The paper employs the theory of Social Construction of Technology (SCOT) that emphasizes the way our actions and discourses shape technology. We argue that a number of active Twitter users, for a variety of motives including financial ones, are shaping the discourse about blockchain by mostly framing it as a positive development in the global market, allegedly creating a revolution in the financial sector. More importantly, the social construction of technology on Twitter does not seem to be exclusively organic, for it includes bots and online spammers who mostly tweet promotional blockchain hashtags.

Social Media and Research Publication Activity During Early Stages of the COVID-19 Pandemic: Longitudinal Trend Analysis.

BackgroundThe COVID-19 pandemic has highlighted the importance of rapid dissemination of scientific and medical discoveries. Current platforms available for the distribution of scientific and clinical research data and information include preprint repositories and traditional peer-reviewed journals. In recent times, social media has emerged as a helpful platform to share scientific and medical discoveries.ObjectiveThis study aimed to comparatively analyze activity on social media (specifically, Twitter) and that related to publications in the form of preprint and peer-reviewed journal articles in the context of COVID-19 and gastroenterology during the early stages of the COVID-19 pandemic.MethodsCOVID-19–related data from Twitter (tweets and user data) and articles published in preprint servers (bioRxiv and medRxiv) as well as in the PubMed database were collected and analyzed during the first 6 months of the pandemic, from December 2019 through May 2020. Global and regional geographic and gastrointestinal organ–specific social media trends were compared to preprint and publication activity. Any relationship between Twitter activity and preprint articles published and that between Twitter activity and PubMed articles published overall, by organ system, and by geographic location were identified using Spearman’s rank-order correlation.ResultsOver the 6-month period, 73,079 tweets from 44,609 users, 7164 journal publications, and 4702 preprint publications were retrieved. Twitter activity (ie, number of tweets) peaked in March 2020, whereas preprint and publication activity (ie, number of articles published) peaked in April 2020. Overall, strong correlations were identified between trends in Twitter activity and preprint and publication activity (P<.001 for both). COVID-19 data across the three platforms mainly concentrated on pulmonology or critical care, but when analyzing the field of gastroenterology specifically, most tweets pertained to pancreatology, most publications focused on hepatology, and most preprints covered hepatology and luminal gastroenterology. Furthermore, there were significant positive associations between trends in Twitter and publication activity for all gastroenterology topics (luminal gastroenterology: P=.009; hepatology and inflammatory bowel disease: P=.006; gastrointestinal endoscopy: P=.007), except pancreatology (P=.20), suggesting that Twitter activity did not correlate with publication activity for this topic. Finally, Twitter activity was the highest in the United States (7331 tweets), whereas PubMed activity was the highest in China (1768 publications).ConclusionsThe COVID-19 pandemic has highlighted the potential of social media as a vehicle for disseminating scientific information during a public health crisis. Sharing and spreading information on COVID-19 in a timely manner during the pandemic has been paramount; this was achieved at a much faster pace on social media, particularly on Twitter. Future investigation could demonstrate how social media can be used to augment and promote scholarly activity, especially as the world begins to increasingly rely on digital or virtual platforms. Scientists and clinicians should consider the use of social media in augmenting public awareness regarding their scholarly pursuits.

Geospatial analysis of misinformation in COVID-19 related tweets

COVID-19 has emerged as a global pandemic caused by its highly transmissible nature during the incubation period. In the absence of vaccination, containment is seen as the best strategy to stop virus diffusion. However, public awareness has been adversely affected by discourses in social media that have downplayed the severity of the virus and disseminated false information. This article investigates COVID-19 related Twitter activity in May and June 2020 to examine the origin and nature of misinformation and its relationship with the COVID-19 incidence rate at the state and county level. A geodatabase of all geotagged COVID-19 related tweets was compiled. Multiscale Geographically Weighted Regression was employed to examine the association between social media activity and the spatial variability of disease incidence. Findings suggest that MGWR could explain 80% of the COVID-19 incidence rate variations indicating a strong spatial relationship between social media activity and spread of the Covid-19 virus. Discourse analysis was conducted on tweets to index tweets downplaying the pandemic or disseminating misinformation. Findings indicate that sites of Twitter misinformation showed more resistance to pandemic management measures in May and June 2020 later experienced a rise in the number of cases in July.

Office of the citizen: a qualitative analysis of Twitter activity during the Lekki shooting in Nigeria’s #EndSARS protests

ABSTRACT In recent times, SNSs have been influential in re-shaping social movements. Not only do they allow access to cheaper and quicker mobilization resources for demonstrators, they also allow them to circumvent conventional communication networks to create their own narratives and thus gain communicative power. Therefore, the study explores the Twitter activities of the #EndSARS protesters in Nigeria on the night of the Lekki shooting with the specific objective of evaluating the role of influencers within the movement as well as establishing the various manifestations and expressions of anger or hope as tweeted by participants in the protests. The study discovered that users relied more on foreign media than local media for coverage while Nigerians in diaspora fueled information spreading about the protests on the night of the shooting.

Developing A Group Model Building Causal Loop Diagram to Understand Millennial Generation Trust in Twitter as Early Warning System for Natural Disaster

Nowadays, Twitter is used as an Early Warning System (EWS) for disasters because of the speed and many users. Based on Asosiasi Penyedia Jasa Internet Indonesia (APJII) data, in 2017, almost 50% of internet users in Indonesia are born in 1983-1998. They are called the millennial generation. Therefore, this study aims to explore the trust of millennials towards Twitter as an EWS. This study utilizes the conceptual model from System Dynamics named Causal Loop Diagram (CLD) to identify the factors and the causal relationship among millennials' factors to trust Twitter as an EWS. It involves ten participants from the millennial generation, consisting of five passive Twitter users and five active Twitter users. A semi-structured interview was conducted with all participants to build the initial CLD gathered from each participant's perspective. Afterward, the initial CLD was verified by all participants through Focus Group Discussion. A group model building CLD that represents the influencing factors and their causal relationship of millennial generation trust in Twitter as EWS for a natural disaster is successfully developed from this study. The tweet frequency, the number of followers, the account credibility, the verified account, the level of trust in social media, and the content quality are considered the underlying factors of active and passive users to trust in Twitter as an EWS natural disaster.