Japanese conservative messages propagate to moderate users better than their liberal counterparts on Twitter.
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ABSTRACT:
SUBMITTER: Yoshida M
PROVIDER: S-EPMC8488035 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:OBJECTIVE:This study explores the presence and actions of an electronic cigarette (e-cigarette) brand, Blu, on Twitter to observe how marketing messages are sent and diffused through the retweet (i.e., message forwarding) functionality. Retweet networks enable messages to reach additional Twitter users beyond the sender's local network. We follow messages from their origin through multiple retweets to identify which messages have more reach, and the different users who are exposed. METHODS:We collected three months of publicly available data from Twitter. A combination of techniques in social network analysis and content analysis were applied to determine the various networks of users who are exposed to e-cigarette messages and how the retweet network can affect which messages spread. RESULTS:The Blu retweet network expanded during the study period. Analysis of user profiles combined with network cluster analysis showed that messages of certain topics were only circulated within a community of e-cigarette supporters, while other topics spread further, reaching more general Twitter users who may not support or use e-cigarettes. CONCLUSIONS:Retweet networks can serve as proxy filters for marketing messages, as Twitter users decide which messages they will continue to diffuse among their followers. As certain e-cigarette messages extend beyond their point of origin, the audience being exposed expands beyond the e-cigarette community. Potential implications for health education campaigns include utilizing Twitter and targeting important gatekeepers or hubs that would maximize message diffusion.
| S-EPMC4694088 | biostudies-literature
Project description:People tend to interpret political information in a manner that confirms their prior beliefs, a cognitive bias that contributes to rising political polarization. In this study, we combined functional magnetic resonance imaging with semantic content analyses to investigate the neural mechanisms that underlie the biased processing of real-world political content. We scanned American participants with conservative-leaning or liberal-leaning immigration attitudes while they watched news clips, campaign ads, and public speeches related to immigration policy. We searched for evidence of "neural polarization": activity in the brain that diverges between people who hold liberal versus conservative political attitudes. Neural polarization was observed in the dorsomedial prefrontal cortex (DMPFC), a brain region associated with the interpretation of narrative content. Neural polarization in the DMPFC intensified during moments in the videos that included risk-related and moral-emotional language, highlighting content features most likely to drive divergent interpretations between conservatives and liberals. Finally, participants whose DMPFC activity closely matched that of the average conservative or the average liberal participant were more likely to change their attitudes in the direction of that group's position. Our work introduces a multimethod approach to study the neural basis of political cognition in naturalistic settings. Using this approach, we characterize how political attitudes biased information processing in the brain, the language most likely to drive polarized neural responses, and the consequences of biased processing for attitude change. Together, these results shed light on the psychological and neural underpinnings of how identical information is interpreted differently by conservatives and liberals.
| S-EPMC7959490 | biostudies-literature
Project description:BackgroundWhat impact gene loss has on the evolution of developmental processes, and how function shuffling has affected retained genes driving essential biological processes, remain open questions in the fields of genome evolution and EvoDevo. To investigate these problems, we have analyzed the evolution of the Wnt ligand repertoire in the chordate phylum as a case study.ResultsWe conduct an exhaustive survey of Wnt genes in genomic databases, identifying 156 Wnt genes in 13 non-vertebrate chordates. This represents the most complete Wnt gene catalog of the chordate subphyla and has allowed us to resolve previous ambiguities about the orthology of many Wnt genes, including the identification of WntA for the first time in chordates. Moreover, we create the first complete expression atlas for the Wnt family during amphioxus development, providing a useful resource to investigate the evolution of Wnt expression throughout the radiation of chordates.ConclusionsOur data underscore extraordinary genomic stasis in cephalochordates, which contrasts with the liberal and dynamic evolutionary patterns of gene loss and duplication in urochordate genomes. Our analysis has allowed us to infer ancestral Wnt functions shared among all chordates, several cases of function shuffling among Wnt paralogs, as well as unique expression domains for Wnt genes that likely reflect functional innovations in each chordate lineage. Finally, we propose a potential relationship between the evolution of WntA and the evolution of the mouth in chordates.
| S-EPMC6060547 | biostudies-literature
Project description:The increasing usage of social media for conversations, together with the availability of its data to researchers, provides an opportunity to study human conversations on a large scale. Twitter, which allows its users to post messages of up to a limit of 140 characters, is one such social media. Previous studies of utterances in books, movies and Twitter have shown that most of these utterances, when transcribed, are much shorter than 140 characters. Furthermore, the median length of Twitter messages was found to vary across US states. Here, we investigate whether the length of Twitter messages varies across different regions in the UK. We find that the median message length, depending on grouping, can differ by up to 2 characters.
| S-EPMC4390308 | biostudies-literature
Project description:Drawing on previous literature that valence and arousal constitute the fundamental properties of emotions and that emotional content is a determinant of social transmission, this study examines the role of valence and arousal in the social transmission of politicians' messages on Twitter. For over 3,000 tweets from five Austrian party leaders, the discrete emotion that the message intended to elicit in its recipients was captured by human coders and then classified on its valence (positive or negative) and arousal (low or high). We examined the effects of valence and arousal on the retweet probability of messages. Results indicate that tweets eliciting a negative (vs. positive) valence decreased retweet probability, whereas tweets eliciting a high (vs. low) arousal increased retweet probability. The present research replicates previous findings that arousal constitutes a determinant of social transmission but extends this mechanism to the realm of political communication on Twitter. Moreover, in contrast to the frequently mentioned negativity bias, positive emotions increased the likelihood of a message being shared in this study.
| S-EPMC9692101 | biostudies-literature
Project description:The 2008 financial crisis unveiled the intrinsic failures of the financial system as we know it. As a consequence, impact investing started to receive increasing attention, as evidenced by the high market growth rates. The goal of impact investment is to generate social and environmental impact alongside a financial return. In this paper we identify the main players in the sector and how they interact and communicate with each other. We use Twitter as a proxy of the impact investing market, and analyze relevant tweets posted over a period of ten months. We apply network, contents and sentiment analysis on the acquired dataset.Our study shows that Twitter users exhibit favourable leaning (predominantly neutral or positive) towards impact investing. Retweet communities are decentralised and include users from a variety of sectors. Despite some basic common vocabulary used by all retweet communities identified, the vocabulary and the topics discussed by each community vary largely. We note that an additional effort should be made in raising awareness about the sector, especially by policymakers and media outlets. The role of investors and the academia is also discussed, as well as the emergence of hybrid business models within the sector and its connections to the tech industry. This paper extends our previous study, one of the first analyses of Twitter activities in the impact investing market.
| S-EPMC6214330 | biostudies-other
Project description:BackgroundDespite concerns about their health risks, e‑cigarettes have gained popularity in recent years. Concurrent with the recent increase in e‑cigarette use, social media sites such as Twitter have become a common platform for sharing information about e-cigarettes and to promote marketing of e‑cigarettes. Monitoring the trends in e‑cigarette-related social media activity requires timely assessment of the content of posts and the types of users generating the content. However, little is known about the diversity of the types of users responsible for generating e‑cigarette-related content on Twitter.ObjectiveThe aim of this study was to demonstrate a novel methodology for automatically classifying Twitter users who tweet about e‑cigarette-related topics into distinct categories.MethodsWe collected approximately 11.5 million e‑cigarette-related tweets posted between November 2014 and October 2016 and obtained a random sample of Twitter users who tweeted about e‑cigarettes. Trained human coders examined the handles' profiles and manually categorized each as one of the following user types: individual (n=2168), vaper enthusiast (n=334), informed agency (n=622), marketer (n=752), and spammer (n=1021). Next, the Twitter metadata as well as a sample of tweets for each labeled user were gathered, and features that reflect users' metadata and tweeting behavior were analyzed. Finally, multiple machine learning algorithms were tested to identify a model with the best performance in classifying user types.ResultsUsing a classification model that included metadata and features associated with tweeting behavior, we were able to predict with relatively high accuracy five different types of Twitter users that tweet about e‑cigarettes (average F1 score=83.3%). Accuracy varied by user type, with F1 scores of individuals, informed agencies, marketers, spammers, and vaper enthusiasts being 91.1%, 84.4%, 81.2%, 79.5%, and 47.1%, respectively. Vaper enthusiasts were the most challenging user type to predict accurately and were commonly misclassified as marketers. The inclusion of additional tweet-derived features that capture tweeting behavior was found to significantly improve the model performance-an overall F1 score gain of 10.6%-beyond metadata features alone.ConclusionsThis study provides a method for classifying five different types of users who tweet about e‑cigarettes. Our model achieved high levels of classification performance for most groups, and examining the tweeting behavior was critical in improving the model performance. Results can help identify groups engaged in conversations about e‑cigarettes online to help inform public health surveillance, education, and regulatory efforts.
| S-EPMC5635233 | biostudies-literature
Project description:BackgroundBoth negative and positive associations between social networking service (SNS) usage and mental health have been suggested by previous studies; however, their differences by type of SNS and age remain unclear. We addressed this issue based on the frequency of traditional communication such as face-to-face and non-face-to-face communication (e.g., phone, email, and letters).MethodsIn total, 8,576 individuals participated, including 2,543 aged 18-39, 3,048 aged 40-64, and 2,985 aged over 65 years. They were asked to indicate their frequency of SNS usage, both for posting and checking, of LINE (a popular message application in Japan), Facebook, Twitter, and Instagram, with frequent usage defined as posting or checking more than a few times a week. To determine mental health status, WHO-5 (i.e., well-being), K6 (i.e., distress symptoms), and feelings of loneliness were assessed. Multiple and logistic regression analyses were adjusted for the frequency of traditional communication. To avoid type 1 error, a Bonferroni correction of p ≤ 0.002 was applied in the regression models (p = 0.05/18, a number of regression models).ResultsThe most frequently used SNS across the three age groups was LINE; frequent usage (both posting and checking) among older adults was independently associated with better well-being. Frequent posting on Facebook was associated with better well-being in middle-aged adults. Young adults who frequently checked on Instagram showed a tendency toward better well-being and lower distress symptoms. On the contrary, frequent usage of Twitter was associated with distress symptoms or feelings of loneliness across all three age groups.ConclusionsWe found generational and SNS-type-dependent negative and positive associations between SNS use and mental health, indicating the possible influences of SNS use and the importance of non-SNS communication.
| S-EPMC7928453 | biostudies-literature
Project description: Not available
| S-EPMC6474041 | biostudies-literature
Project description:BackgroundPharmacists are often depicted as dispensers of medication as opposed to health professionals who provide patient care. Our objective was to identify how pharmacists' roles were portrayed in images on Twitter for World Pharmacists Day (WPD) 2020.MethodsA qualitative content analysis was undertaken to evaluate the images of pharmacists on WPD. Tweets were included that had a photo or image, used 1 of 5 WPD hashtags and were posted between September 24 and 26, 2020. Thematic analysis was performed independently by 2 investigators. Tweets were categorized into 5 groups: 1) drug distribution roles, 2) patient care roles, 3) no described roles, 4) not professional/unprofessional roles and 5) not relevant. Subgroup analysis was performed for the users who posted the tweets.ResultsOf the 970 tweets analyzed, only 11% of the overall tweets portrayed the patient care roles of pharmacists, whereas 51% portrayed drug distribution roles and 29% did not describe any particular roles of pharmacists. These proportions were similar between subgroups of tweeters.DiscussionWPD is intended to promote and advocate for the pharmacy profession. The results of our study show poor messaging of pharmacists' roles and reflect a missed opportunity to showcase the full scope of pharmacy practice.ConclusionBased on the images tweeted on WPD 2020, the diversity of pharmacists' practice as skilled health care practitioners was lost in a sea of tweets portraying pharmacists' roles in drug distribution. We hope that pharmacists and pharmacy organizations will awaken to this self-induced problem for WPD 2021. Can Pharm J (Ott) 2021;154(5):xx-xx.
| S-EPMC8408907 | biostudies-literature