Tweet content

This paper presents a novel approach for detecting abuse on Twitter. Abusive posts have become a major problem for social media platforms like Twitter. It is important to identify abuse to mitigate its potential harm. Many researchers have proposed methods to detect abuse on Twitter. However, most of the existing approaches for detecting abuse look only at the content of the abusive tweet in isolation and do not consider its contextual information, particularly the tweets posted before the abusive tweet. In this paper, we propose a new method for detecting abuse that uses contextual information from the tweets that precede and follow the abusive tweet...

Reports an error in "Digital traces of offline mobilization" by Laura G. E. Smith, Lukasz Piwek, Joanne Hinds, Olivia Brown and Adam Joinson ( Journal of Personality and Social Psychology , 2023[Sep], Vol 125[3], 496-518). The following article is being corrected: https://doi.org/10.1037/pspa0000338. Cangxiong Chen is added as the fifth author in the byline and author note. Cangxiong Chen's ORCID ID is now included in the author note. The CRediT paragraph in the author note now includes Cangxiong Chen's supporting role for the article...

OBJECTIVE: To analyze the effect of visual abstracts versus automated tweets on social media participation in Otology & Neurotology. PATIENTS: N/A. INTERVENTIONS: Introduction of visual abstracts developed by the social media editorial team to established automated tweets created by the dlvr.it computer program on the Otology & Neurotology Twitter account. MAIN OUTCOME MEASURES: Twitter analytics including the number of new followers per month, impressions per tweet, and engagements per tweet...

Natural language understanding (NLU) is integral to various social media applications. However, the existing NLU models rely heavily on context for semantic learning, resulting in compromised performance when faced with short and noisy social media content. To address this issue, we leverage in-context learning (ICL), wherein language models learn to make inferences by conditioning on a handful of demonstrations to enrich the context and propose a novel hashtag-driven ICL (HICL) framework. Concretely, we pretrain a model, which employs #hashtags (user-annotated topic labels) to drive BERT-based pretraining through contrastive learning...

This paper provides an extensive examination of a sizable dataset of English tweets focusing on nine widely recognized cryptocurrencies, specifically Cardano, Binance, Bitcoin, Dogecoin, Ethereum, Fantom, Matic, Shiba, and Ripple. Our goal was to conduct a psycholinguistic and emotional analysis of social media content associated with these cryptocurrencies. Such analysis can enable researchers and experts dealing with cryptocurrencies to make more informed decisions. Our work involved comparing linguistic characteristics across the diverse digital coins, shedding light on the distinctive linguistic patterns emerging in each coin's community...

Transit providers have used social media (e.g., Twitter) as a powerful platform to shape public perception and provide essential information, especially during times of disruption and disaster. This work examines how transit agencies used Twitter during the COVID-19 pandemic to communicate with riders and how the content and general activity influence rider interaction and Twitter handle popularity. We analyzed 654,345 tweets generated by the top 40 transit agencies in the US, based on Vehicles Operated in Annual Maximum Service (VOM), from January 2020 to August 2021...

INTRODUCTION: When using social media, physicians are encouraged and trained to maintain separate professional and personal identities. However, this separation is difficult and even undesirable, as the blurring of personal and professional online presence can influence patient trust. Thus, it is necessary to develop policies and educational resources that are more responsive to the blurring of personal and professional boundaries on social media. This study aims to provide an understanding of how physicians present themselves holistically online to inform such policies and resources...

CONTEXT.—: Social media is a powerful tool in pathology education and professional networking that connects pathologists and pathology trainees from around the world. Twitter (X) appears to be the most popular social media platform pathologists use to share pathology-related content and connect with other pathologists. Although there has been some published research on pathology-related activity on Twitter during short time frames, to date there has not been published research examining pathology-related Twitter activity in totality from its earliest days of activity to recently...

INTRODUCTION: Urticaria is a common debilitating dermatological disorder impairing a patient's quality of life. Such patients are increasingly using socialmedia to manage their health and interact with peers, particularly during the ongoing COVID-19 pandemic. OBJECTIVES: To explore and analyse the quality of urticaria related social-media information available to patients. MATERIALS AND METHODS: An in-depth data audit of the three most commonly used social networks viz...

BACKGROUND: Analysis of X (formerly Twitter) posts can inform on the interest/perceptions that social media users have on health subjects. In this study, we aimed to analyse tweets on allergic conditions, comparing them with surveillance data. METHODS: We retrieved tweets from England on "allergy," "asthma," and "allergic rhinitis," published between 2016 and 2021. We estimated the correlation between the frequency of tweets on "asthma" and "allergic rhinitis" and English surveillance data on the incidence of asthma and allergic rhinitis medical visits...

INTRODUCTION: Cocaine abuse represents a major public health concern. The social perception of cocaine has been changing over the decades, a phenomenon closely tied to its patterns of use and abuse. Twitter is a valuable tool to understand the status of drug use and abuse globally. However, no specific studies discussing cocaine have been conducted on this platform. METHODS: 111,508 English and Spanish tweets containing "cocaine" from 2018 to 2022 were analyzed...

OBJECTIVES: To synthesize discussions among sexual minority men and gender diverse (SMMGD) individuals on mpox, given limited representation of SMMGD voices in existing mpox literature. METHODS: BERTopic (a topic modeling technique) was employed with human validations to analyze mpox-related tweets ( n = 8,688; October 2020-September 2022) from 2,326 self-identified SMMGD individuals in the U.S.; followed by content analysis and geographic analysis. RESULTS: BERTopic identified 11 topics: health activism (29...

BACKGROUND: A silver lining to the COVID-19 pandemic is that it cast a spotlight on a long-underserved group. The barrage of attacks against older Asian Americans during the crisis galvanized society into assisting them in various ways. On Twitter, now known as X, support for them coalesced around the hashtag #ProtectOurElders. To date, discourse surrounding older Asian Americans has escaped the attention of gerontologists-a gap we seek to fill. Our study serves as a reflection of the level of support that has been extended to older Asian Americans, even as it provides timely insights that will ultimately advance equity for them...

BACKGROUND: Many individuals eligible for statin therapy decline treatment, often due to fear of adverse effects. Misinformation about statins is common and drives statin reluctance, but its prevalence on social media platforms, such as Twitter (now X) remains unclear. Social media bots are known to proliferate medical misinformation, but their involvement in statin-related discourse is unknown. This study examined temporal trends in volume, author type (bot or human), and sentiment of statin-related Twitter posts (tweets)...

BACKGROUND: Conversations around disease conducted through social media provide a means for capturing public perspectives that may be useful in considering public health approaches. Syphilis is a sexually transmitted disease that is re-emerging. We sought to characterise online discourse on syphilis using data collected from the social media platform, Twitter. METHODS: We extracted English-language tweets containing the word 'syphilis' posted on Twitter in 2019...

BACKGROUND: The proliferation of social media platforms has provided a unique space for discourse on mental health, originally intended to destigmatize mental illness. However, recent discourses on these platforms have shown a concerning shift towards the romanticization of mental health issues. This research focuses on Twitter (now called X) users' authentic discussions on the phenomenon of romanticizing mental health, aiming to uncover unique perspectives, themes, and language used by users when engaging with this complex topic...

Social movements and their respective countermovements have evolved to use online social media platforms to recruit followers, share pertinent information, discuss relevant issues, and draw the attention of political figures. Movements' strategic use of Twitter has increasingly been studied, though there are relatively few studies that compare social movements and their corresponding countermovements simultaneously. We examine engagement in the #DefundthePolice social movement and #DefendthePolice countermovement in a Twitter network comprised of retweets using both hashtags from August 2020 to January 2021...

BACKGROUND: Social media has the potential to be of great value in understanding patterns in public health using large-scale analysis approaches (eg, data science and natural language processing [NLP]), 2 of which have been used in public health: sentiment analysis and topic modeling; however, their use in the area of food security and public health nutrition is limited. OBJECTIVE: This study aims to explore the potential use of NLP tools to gather insights from real-world social media data on the public health issue of food security...

<b/> Background : Between April 7 and 14, 2019, the "Breaking the Silence" media engagement campaign was launched in Oregon. Aims: We aimed to assess the consistency of media content related to the campaign with media guidelines and the quantitative footprint on Twitter (now X) over time. Method: Media items related to the campaign were analyzed regarding focus and consistency with media guidelines for suicide reporting and compared with other suicide-related reports published in the same time frame, as well as with reporting in Washington, the control region...

OBJECTIVE: The study delves into the social identity of pro-vaccination and anti-vaccination supporters, emphasizing an understanding of the values that shape these distinct identities. Furthermore, the research highlights that user-generated content pertaining to vaccines offers valuable insights into the underlying personal values of both pro-vaccination and anti-vaccination groups. METHOD: We constructed a textual dataset based on 142,596 tweets. This data have been analyzed in three steps...