Stylistic variation on the Donald Trump Twitter account: A linguistic analysis of tweets posted between 2009 and 2018.
Ontology highlight
ABSTRACT:
SUBMITTER: Clarke I
PROVIDER: S-EPMC6760825 | biostudies-literature | 2019
REPOSITORIES: biostudies-literature
Publications
Stylistic variation on the Donald Trump Twitter account: A linguistic analysis of tweets posted between 2009 and 2018.
Clarke Isobelle I Grieve Jack J
PloS one 20190925 9
Twitter was an integral part of Donald Trump's communication platform during his 2016 campaign. Although its topical content has been examined by researchers and the media, we know relatively little about the style of the language used on the account or how this style changed over time. In this study, we present the first detailed description of stylistic variation on the Trump Twitter account based on a multivariate analysis of grammatical co-occurrence patterns in tweets posted between 2009 an ...[more]
Similar Datasets
Project description:Measuring and forecasting opinion trends from real-time social media is a long-standing goal of big-data analytics. Despite the large amount of work addressing this question, there has been no clear validation of online social media opinion trend with traditional surveys. Here we develop a method to infer the opinion of Twitter users by using a combination of statistical physics of complex networks and machine learning based on hashtags co-occurrence to build an in-domain training set of the order of a million tweets. We validate our method in the context of 2016 US Presidential Election by comparing the Twitter opinion trend with the New York Times National Polling Average, representing an aggregate of hundreds of independent traditional polls. The Twitter opinion trend follows the aggregated NYT polls with remarkable accuracy. We investigate the dynamics of the social network formed by the interactions among millions of Twitter supporters and infer the support of each user to the presidential candidates. Our analytics unleash the power of Twitter to uncover social trends from elections, brands to political movements, and at a fraction of the cost of traditional surveys.
| S-EPMC5989214 | biostudies-literature
Project description:BackgroundSurveys are popular methods to measure public perceptions in emergencies but can be costly and time consuming. We suggest and evaluate a complementary "infoveillance" approach using Twitter during the 2009 H1N1 pandemic. Our study aimed to: 1) monitor the use of the terms "H1N1" versus "swine flu" over time; 2) conduct a content analysis of "tweets"; and 3) validate Twitter as a real-time content, sentiment, and public attention trend-tracking tool.Methodology/principal findingsBetween May 1 and December 31, 2009, we archived over 2 million Twitter posts containing keywords "swine flu," "swineflu," and/or "H1N1." using Infovigil, an infoveillance system. Tweets using "H1N1" increased from 8.8% to 40.5% (R(2) = .788; p<.001), indicating a gradual adoption of World Health Organization-recommended terminology. 5,395 tweets were randomly selected from 9 days, 4 weeks apart and coded using a tri-axial coding scheme. To track tweet content and to test the feasibility of automated coding, we created database queries for keywords and correlated these results with manual coding. Content analysis indicated resource-related posts were most commonly shared (52.6%). 4.5% of cases were identified as misinformation. News websites were the most popular sources (23.2%), while government and health agencies were linked only 1.5% of the time. 7/10 automated queries correlated with manual coding. Several Twitter activity peaks coincided with major news stories. Our results correlated well with H1N1 incidence data.ConclusionsThis study illustrates the potential of using social media to conduct "infodemiology" studies for public health. 2009 H1N1-related tweets were primarily used to disseminate information from credible sources, but were also a source of opinions and experiences. Tweets can be used for real-time content analysis and knowledge translation research, allowing health authorities to respond to public concerns.
| S-EPMC2993925 | biostudies-literature
Project description:Pathological narcissism is a term often applied to former President Donald Trump, but it has been less examined as a potential predictor of voting for him. Trump projects a grandiose and omnipotent self-image during press conferences and rallies, and his followers at these events often respond with both effusive admiration and an inflated sense of their own self-regard, all of which are aspects of narcissism. However, while Trump's personal narcissism has been well documented, there is little research on the narcissism of his supporters. In this study we conducted an exploratory analysis examining the hierarchical structure of pathological narcissism and which aspects of narcissism within that structure were associated with intended voting for Trump in the 2020 U.S. presidential election in a sample of U.S. residents collected online (N = 495) using Amazon's Mechanical Turk. Results indicated that an eight-echelon hierarchy best fit the data. Within this hierarchy, antagonistic and indifferent aspects of narcissism within the fifth echelon best predicted intended voting for Trump over and above relevant demographic variables. These results have implications for the study of narcissism and, especially given the results of the 2020 election, the degree to which one can make use of narcissistic aspects of personality in political contests.
| S-EPMC8049239 | biostudies-literature
Project description:MotivationMicro-blogging with Twitter to communicate new results, discuss ideas and share techniques is becoming central. While most Twitter users are real people, the Twitter API provides the opportunity to develop Twitter bots and to analyze global trends in tweets.ResultsEnrichrBot is a bot that tracks and tweets information about human genes implementing six principal functions: (i) tweeting information about under-studied genes including non-coding lncRNAs, (ii) replying to requests for information about genes, (iii) responding to GWASbot, another bot that tweets Manhattan plots from genome-wide association study analysis of the UK Biobank, (iv) tweeting randomly selected gene sets from the Enrichr database for analysis with Enrichr, (v) responding to mentions of human genes in tweets with additional information about these genes and (vi) tweeting a weekly report about the most trending genes on Twitter.Availability and implementationhttps://twitter.com/botenrichr; source code: https://github.com/MaayanLab/EnrichrBot.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC7320605 | biostudies-literature
Project description:Te reo Māori, the Indigenous language of Aotearoa New Zealand, is a distinctive feature of the nation's cultural heritage. This paper documents our efforts to build a corpus of 79,000 Māori-language tweets using computational methods. The Reo Māori Twitter (RMT) Corpus was created by targeting Māori-language users identified by the Indigenous Tweets website, pre-processing their data and filtering out non-Māori tweets, together with other sources of noise. Our motivation for creating such a resource is three-fold: (1) it serves as a rich and unique dataset for linguistic analysis of te reo Māori on social media; (2) it can be used as training data to develop and augment Natural Language Processing (NLP) tools with robust, real-world Māori-language applications; and (3) it will potentially promote awareness of, and encourage positive interaction with, the growing community of Māori tweeters, thereby increasing the use and visibility of te reo Māori in an online environment. While the corpus captures data from 2007 to 2020, our analysis shows that the number of tweets in the RMT Corpus peaked in 2014, and the number of active tweeters peaked in 2017, although at least 600 users were still active in 2020. To the best of our knowledge, the RMT Corpus is the largest publicly-available collection of social media data containing (almost) exclusively Māori text, making it a useful resource for language experts, NLP developers and Indigenous researchers alike.Supplementary informationThe online version contains supplementary material available at 10.1007/s10579-022-09580-w.
| S-EPMC8852919 | biostudies-literature
Project description:BackgroundTwitter is becoming an increasingly important avenue for people to seek information about HIV prevention. Tweets about HIV prevention may reflect or influence current norms about the acceptability of different HIV prevention methods. Therefore, it may be useful to empirically investigate trends in the level of attention paid to different HIV prevention topics on Twitter over time.ObjectiveThe primary objective of this study was to investigate temporal trends in the frequency of tweets about different HIV prevention topics on Twitter between 2014 and 2019.MethodsWe used the Twitter application programming interface to obtain English-language tweets employing #HIVPrevention between January 1, 2014, and December 31, 2019 (n=69,197, globally). Using iterative qualitative content analysis on samples of tweets, we developed a keyword list to categorize the tweets into 10 prevention topics (eg, condom use, preexposure prophylaxis [PrEP]) and compared the frequency of tweets mentioning each topic over time. We assessed the overall change in the proportions of #HIVPrevention tweets mentioning each prevention topic in 2019 as compared with 2014 using chi-square and Fisher exact tests. We also conducted descriptive analyses to identify the accounts posting the most original tweets, the accounts retweeted most frequently, the most frequently used word pairings, and the spatial distribution of tweets in the United States compared with the number of state-level HIV cases.ResultsPrEP (13,895 tweets; 20.08% of all included tweets) and HIV testing (7688, 11.11%) were the most frequently mentioned topics, whereas condom use (2941, 4.25%) and postexposure prophylaxis (PEP; 823, 1.19%) were mentioned relatively less frequently. The proportions of tweets mentioning PrEP (327/2251, 14.53%, in 2014, 5067/12,971, 39.1%, in 2019; P≤.001), HIV testing (208/2251, 9.24%, in 2014, 2193/12,971, 16.91% in 2019; P≤.001), and PEP (25/2251, 1.11%, in 2014, 342/12,971, 2.64%, in 2019; P≤.001) were higher in 2019 compared with 2014, whereas the proportions of tweets mentioning abstinence, condom use, circumcision, harm reduction, and gender inequity were lower in 2019 compared with 2014. The top retweeted accounts were mostly UN-affiliated entities; celebrities and HIV advocates were also represented. Geotagged #HIVPrevention tweets in the United States between 2014 and 2019 (n=514) were positively correlated with the number of state-level HIV cases in 2019 (r=0.81, P≤.01).ConclusionsTwitter may be a useful source for identifying HIV prevention trends. During our evaluation period (2014-2019), the most frequently mentioned prevention topics were PrEP and HIV testing in tweets using #HIVPrevention. Strategic responses to these tweets that provide information about where to get tested or how to obtain PrEP may be potential approaches to reduce HIV incidence.
| S-EPMC9412898 | biostudies-literature
Project description:The 2016 United States presidential election was exceptional for many reasons; most notably the extreme division between supporters of Donald Trump and Hillary Clinton. In an election that turned more upon the character traits of the candidates than their policy positions, there is reason to believe that the non-verbal performances of the candidates influenced attitudes toward the candidates. Two studies, before Election Day, experimentally tested the influence of Trump's micro-expressions of fear during his Republican National Convention nomination acceptance speech on how viewers evaluated his key leadership traits of competence and trustworthiness. Results from Study 1, conducted 3 weeks prior to the election, indicated generally positive effects of Trump's fear micro-expressions on his trait evaluations, particularly when viewers were first exposed to his opponent, Clinton. In contrast, Study 2, conducted 4 days before Election Day, suggests participants had at that point largely established their trait perceptions and were unaffected by the micro-expressions.
| S-EPMC8206780 | biostudies-literature
Project description:BackgroundThe sale of electronic cigarettes (e-cigarettes) containing nicotine is prohibited in all Australian states and territories; yet, the growing availability and convenience of the internet enable the promotion and exposure of e-cigarettes across countries. Social media's increasing pervasiveness has provided a powerful avenue to market products and influence social norms and risk behaviors. At present, there is no evidence of how e-cigarettes and vaping are promoted on social media in Australia.ObjectiveThis study aimed to investigate how e-cigarettes are portrayed and promoted on Twitter through a content analysis of vaping-related tweets containing an image posted and retweeted by Australian users and how the portrayal and promotion have emerged and trended over time.MethodsIn total, we analyzed 1303 tweets and accompanying images from 2012, 2014, 2016, and 2018 collected through the Tracking Infrastructure for Social Media Analysis (TrISMA), a contemporary technical and organizational infrastructure for the tracking of public communication by Australian users of social media, via a list of 15 popular e-cigarette-related terms.ResultsDespite Australia's cautious approach toward e-cigarettes and the limited evidence supporting them as an efficacious smoking cessation aid, it is evident that there is a concerted effort by some Twitter users to promote these devices as a health-conducive (91/129, 70.5%), smoking cessation product (266/1303, 20.41%). Further, Twitter is being used in an attempt to circumvent Australian regulation and advocate for a more liberal approach to personal vaporizers (90/1303, 6.90%). A sizeable proportion of posts was dedicated to selling or promoting vape products (347/1303, 26.63%), and 19.95% (260/1303) were found to be business listings. These posts used methods to try and expand their clientele further than immediate followers by touting competitions and giveaways, with those wanting to enter having to perform a sequence of steps such as liking, tagging, and reposting, ultimately exposing the post among the user's network and to others not necessarily interested in vaping.ConclusionsThe borderless nature of social media presents a clear challenge for enforcing Article 13 of the World Health Organization Framework Convention on Tobacco Control, which requires all ratifying nations to implement a ban on tobacco advertising, promotion, and sponsorship. Countering the advertising and promotion of these products is a public health challenge that will require cross-border cooperation with other World Health Organization Framework Convention on Tobacco Control parties. Further research aimed at developing strategies to counter the advertising and promotion of e-cigarettes is therefore needed.
| S-EPMC7677022 | biostudies-literature
Project description:BackgroundAs the majority of Twitter content is publicly available, the platform has become a rich data source for public health surveillance, providing insights into emergent phenomena, such as vaping. Although there is a growing body of literature that has examined the content of vaping-related tweets, less is known about the people who generate and disseminate these messages and the role of e-cigarette advocates in the promotion of these devices.ObjectiveThis study aimed to identify key conversation trends and patterns over time, and discern the core voices, message frames, and sentiment surrounding e-cigarette discussions on Twitter.MethodsA random sample of data were collected from Australian Twitter users who referenced at least one of 15 identified e-cigarette related keywords during 2012, 2014, 2016, or 2018. Data collection was facilitated by TrISMA (Tracking Infrastructure for Social Media Analysis) and analyzed by content analysis.ResultsA sample of 4432 vaping-related tweets posted and retweeted by Australian users was analyzed. Positive sentiment (3754/4432, 84.70%) dominated the discourse surrounding e-cigarettes, and vape retailers and manufacturers (1161/4432, 26.20%), the general public (1079/4432, 24.35%), and e-cigarette advocates (1038/4432, 23.42%) were the most prominent posters. Several tactics were used by e-cigarette advocates to communicate their beliefs, including attempts to frame e-cigarettes as safer than traditional cigarettes, imply that federal government agencies lack sufficient competence or evidence for the policies they endorse about vaping, and denounce as propaganda "gateway" claims of youth progressing from e-cigarettes to combustible tobacco. Some of the most common themes presented in tweets were advertising or promoting e-cigarette products (2040/4432, 46.03%), promoting e-cigarette use or intent to use (970/4432, 21.89%), and discussing the potential of e-cigarettes to be used as a smoking cessation aid or tobacco alternative (716/4432, 16.16%), as well as the perceived health and safety benefits and consequences of e-cigarette use (681/4432, 15.37%).ConclusionsAustralian Twitter content does not reflect the country's current regulatory approach to e-cigarettes. Rather, the conversation on Twitter generally encourages e-cigarette use, promotes vaping as a socially acceptable practice, discredits scientific evidence of health risks, and rallies around the idea that e-cigarettes should largely be outside the bounds of health policy. The one-sided nature of the discussion is concerning, as is the lack of disclosure and transparency, especially among vaping enthusiasts who dominate the majority of e-cigarette discussions on Twitter, where it is unclear if comments are endorsed, sanctioned, or even supported by the industry.
| S-EPMC7593865 | biostudies-literature
Project description:The Welsh vote for "leave" in the Brexit referendum surprised some academics and analysts due to its strong preference for Labor and its close financial ties to the EU. It also brought up a debate about apparent differences in Welsh and English attitudes towards race, ethnicity, and migration, with the former often claiming to have a more positive stance regarding the presence of ethnic minorities and foreign nationalities. This paper proposes to analyze discourse posted on Twitter during June 2016, specifically targeting Wales and England with the aim to offer insight into the perceptions and beliefs of Welsh and English individuals on the platform and if attitudes on race, ethnicity, and migration played a significant role. Counterfactuals are checked with posts from the first few weeks of the refugee crisis in Afghanistan in 2021, the war on Ukraine, and the announcement of the Rwanda policy. The current discussion of Welsh national identity includes its claims as a "nation of sanctuary" and that understands oppression and marginalization. Thus, Welsh perspectives on Brexit become an interesting viewpoint to comprehending ethnic minorities and foreigners as it creates a possible conflict between the institutional discourse, cultural views, and perceived economic needs. In this context, this paper takes the view that Twitter is an area where individuals post their thoughts uninhibited, and where we can conduct an aggregate analysis of that public sentiment.
| S-EPMC10690362 | biostudies-literature