Social media brand engagement in the context of collaborative consumption: the case of AIRBNB
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ABSTRACT:
SUBMITTER: Schivinski B
PROVIDER: S-EPMC7474324 | biostudies-literature | 2020 Sep
REPOSITORIES: biostudies-literature
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Project description:This study promotes the news repertoire framework as an analytical approach best suited for studying news engagement on social media (SM), considering its multifaceted nature. To demonstrate the theoretical benefits of this proposal, the study seeks to (1) identify user profiles based on SM news viewing and sharing, and news consumption on other platforms; (2) determine profile predictors; and (3) evaluate their possible outcomes. A panel study (N = 1786) demonstrated the emergence of identifiable profiles, attributed to differences in SM use and political interest. In addition, profiles embodied different effects on political participation over time. A second study (N = 86) was conducted thereafter, in which users' Facebook news feed use was analyzed to determine differences in news supply according to profiles. Findings that could not have been achieved using the more common unidimensional news consumption methods are discussed in light of new theoretical gains provided by the repertoire approach.
| S-EPMC9315192 | biostudies-literature
Project description:BackgroundSocial media chatter in 2020 has been largely dominated by the COVID-19 pandemic. Existing research shows that COVID-19 discourse is highly politicized, with political preferences linked to beliefs and disbeliefs about the virus. As it happens with topics that become politicized, people may fall into echo chambers, which is the idea that one is only presented with information they already agree with, thereby reinforcing one's confirmation bias. Understanding the relationship between information dissemination and political preference is crucial for effective public health communication.ObjectiveWe aimed to study the extent of polarization and examine the structure of echo chambers related to COVID-19 discourse on Twitter in the United States.MethodsFirst, we presented Retweet-BERT, a scalable and highly accurate model for estimating user polarity by leveraging language features and network structures. Then, by analyzing the user polarity predicted by Retweet-BERT, we provided new insights into the characterization of partisan users.ResultsWe observed that right-leaning users were noticeably more vocal and active in the production and consumption of COVID-19 information. We also found that most of the highly influential users were partisan, which may contribute to further polarization. Importantly, while echo chambers exist in both the right- and left-leaning communities, the right-leaning community was by far more densely connected within their echo chamber and isolated from the rest.ConclusionsWe provided empirical evidence that political echo chambers are prevalent, especially in the right-leaning community, which can exacerbate the exposure to information in line with pre-existing users' views. Our findings have broader implications in developing effective public health campaigns and promoting the circulation of factual information online.
| S-EPMC8371575 | biostudies-literature
Project description:There has been growing concern about the role social media plays in political polarization. We investigated whether out-group animosity was particularly successful at generating engagement on two of the largest social media platforms: Facebook and Twitter. Analyzing posts from news media accounts and US congressional members (n = 2,730,215), we found that posts about the political out-group were shared or retweeted about twice as often as posts about the in-group. Each individual term referring to the political out-group increased the odds of a social media post being shared by 67%. Out-group language consistently emerged as the strongest predictor of shares and retweets: the average effect size of out-group language was about 4.8 times as strong as that of negative affect language and about 6.7 times as strong as that of moral-emotional language-both established predictors of social media engagement. Language about the out-group was a very strong predictor of "angry" reactions (the most popular reactions across all datasets), and language about the in-group was a strong predictor of "love" reactions, reflecting in-group favoritism and out-group derogation. This out-group effect was not moderated by political orientation or social media platform, but stronger effects were found among political leaders than among news media accounts. In sum, out-group language is the strongest predictor of social media engagement across all relevant predictors measured, suggesting that social media may be creating perverse incentives for content expressing out-group animosity.
| S-EPMC8256037 | biostudies-literature
Project description:The COVID-19 pandemic made explicit the issues of communicating science in an information ecosystem dominated by social media platforms. One of the fundamental communication challenges of our time is to provide the public with reliable content and contrast misinformation. This paper investigates how social media can become an effective channel to promote engagement and (re)build trust. To measure the social response to quality communication, we conducted an experimental study to test a set of science communication recommendations on Facebook and Twitter. The experiment involved communication practitioners and social media managers from select countries in Europe, applying and testing such recommendations for five months. Here we analyse their feedback in terms of adoption and show that some differences emerge across platforms, topics, and recommendation categories. To evaluate these recommendations' effect on users, we measure their response to quality content, finding that the median engagement is generally higher, especially on Twitter. The results indicate that quality communication strategies may elicit positive feedback on social media. A data-driven and co-designed approach in developing counter-strategies is thus promising in tackling misinformation.
| S-EPMC9560150 | biostudies-literature
Project description:There has been a surge in vaccine hesitancy following the Coronavirus pandemic. This study measured the prevalence of and identified factors associated with vaccine hesitancy and social media use. An online survey was administered (n = 1050) between May and July 2021. Chi-square tests were used to examine bivariate associations with vaccine hesitancy (partially vaccinated and unvaccinated participants). Logistic regression was used to identify associations between social media use and vaccine hesitancy. Chi-square tests showed women (69.7% vs 28.2% men, padjusted = .002), African American participants (52.3% vs 17.8% white, padjusted < .001), high school diploma (54.4% vs 38.6% college degree, padjusted < .001), political unaffiliated (15.8% vs 14.5% republican, padjusted < .001), Muslim (10.0% vs 0% Jewish, padjusted < .001), and never married/single (53.9% vs 17.0% married, padjusted < .001) were more likely to be vaccine hesitant. Controlling for all demographic variables (age, race, gender, and education), more frequent use of social media for reading news was associated with lower vaccine hesitancy (OR 0.35, 99% CI 0.20, 0.63, p < 0.001). However, using social media as a source of vaccine information without any other trusted source (health department, doctor, CDC,) was associated with higher odds of being vaccine hesitant (OR 2.00, 99% CI 1.15, 3.46, p = 0.001). People who use social media without referencing trusted sources may be particularly vulnerable to disinformation or vaccine hesitant persons are more likely exposed to non-trusted social media sites as their only information source.
| S-EPMC8947854 | biostudies-literature
Project description:Social media has become a modern arena for human life, with billions of daily users worldwide. The intense popularity of social media is often attributed to a psychological need for social rewards (likes), portraying the online world as a Skinner Box for the modern human. Yet despite such portrayals, empirical evidence for social media engagement as reward-based behavior remains scant. Here, we apply a computational approach to directly test whether reward learning mechanisms contribute to social media behavior. We analyze over one million posts from over 4000 individuals on multiple social media platforms, using computational models based on reinforcement learning theory. Our results consistently show that human behavior on social media conforms qualitatively and quantitatively to the principles of reward learning. Specifically, social media users spaced their posts to maximize the average rate of accrued social rewards, in a manner subject to both the effort cost of posting and the opportunity cost of inaction. Results further reveal meaningful individual difference profiles in social reward learning on social media. Finally, an online experiment (n = 176), mimicking key aspects of social media, verifies that social rewards causally influence behavior as posited by our computational account. Together, these findings support a reward learning account of social media engagement and offer new insights into this emergent mode of modern human behavior.
| S-EPMC7910435 | biostudies-literature
Project description:Recently, we have witnessed the popularity and proliferation of social media applications (e.g., Delicious, Flickr, and YouTube) in the web 2.0 era. The rapid growth of user-generated data results in the problem of information overload to users. Facing such a tremendous volume of data, it is a big challenge to assist the users to find their desired data. To attack this critical problem, we propose the collaborative search approach in this paper. The core idea is that similar users may have common interests so as to help users to find their demanded data. Similar research has been conducted on the user log analysis in web search. However, the rapid growth and change of user-generated data in social media require us to discover a brand-new approach to address the unsolved issues (e.g., how to profile users, how to measure the similar users, and how to depict user-generated resources) rather than adopting existing method from web search. Therefore, we investigate various metrics to identify the similar users (user community). Moreover, we conduct the experiment on two real-life data sets by comparing the Collaborative method with the latest baselines. The empirical results show the effectiveness of the proposed approach and validate our observations.
| S-EPMC4322306 | biostudies-other
Project description:Health promoters have been unable to reach and engage people on social media (SM) to the extent that food industry brands and lifestyle personalities have. The objective of this study was to identify the SM post strategies associated with higher engagement in nutrition and food-related posts using a retrospective content analysis. The six most engaging posts from both Facebook and Instagram's 10 most successful nutrition and food-related accounts were analysed across four fields. Subjective and objective post strategies were coded on 736 posts, and associations with engagement were explored using the Least Absolute Shrinkage and Selection Operator (LASSO). Lifestyle personalities recorded the highest absolute engagement, while health promoters recorded the highest engagement relative to follower count. Strategies associated with higher Facebook engagement included using hashtags and prompting engagement through announcements, while on Instagram, higher engagement was associated with higher caption counts, providing health information links, prompting engagement through strategies that require an action, and using humorous strategies. Strategies associated with lower Instagram engagement included reposted content, general encouragement to eat strategies, encouragement to exercise strategies, not inducing any emotion/hedonic sensations, and providing a negative tone. Health promoters should adapt SM posts to the different SM platforms and utilise strategies associated with higher engagement to engage with their audience on SM.
| S-EPMC7551727 | biostudies-literature
Project description:IntroductionGiven increasing efforts to regulate e-cigarettes, it is important to understand factors associated with support for tobacco regulatory policies. We investigate such factors found in social media and hypothesize that greater online engagement with tobacco content would be associated with less support for e-cigarette regulatory policies.MethodsWe constructed social networks of Twitter users who tweet about tobacco and categorized them using a combination of social network and Twitter metrics. Twitter users were identified as representing leaders, followers or general users in online discussions of tobacco products, and invited to complete an online survey. Participants responded to questions about their engagement with tobacco-related content online, degree of support for e-cigarette regulations, exposure to tobacco marketing, e-cigarette use and other demographic information. We examined links between their reported engagement with tobacco-related content and support for e-cigarette regulatory policies using structural equation modelling.ResultsThe analytic sample consisted of 470 participants. The conceptualized structural equation model had a good fit (χ2 (32) = 24.85, p = 0.09, CFI = 0.99, RMSEA = 0.03). Findings support our hypothesis: engagement with online tobacco content was negatively associated with support for e-cigarette policies, while controlling for e-cigarette use, tobacco marketing exposure, social media use frequency and demographic factors.ConclusionsFindings suggest that our hypothesis was supported. Twitter users engaging with tobacco-related content and harboring negative attitudes toward e-cigarette regulatory policies could be an important audience segment to reach with tailored e-cigarette policy education messages.
| S-EPMC6542731 | biostudies-literature
Project description:Aim: To explore participation with alcohol marketing (i.e. commenting on brand statuses) and user-created promotion on social media (i.e. photos of peers drinking) by young people in the United Kingdom (UK), and what association this has with higher-risk consumption and brand identification. Method: Online cross-sectional survey with 11-19-year olds in the UK (n = 3,399) (average age: 15 years old). Past-month participation was measured for five forms of alcohol marketing on social media and one form of user-created promotion (all Yes/No). Past-month awareness of nine wider alcohol marketing activities, social media apps used at least weekly, and ownership of branded merchandise were included as covariates. Outcomes included higher-risk consumption in current drinkers (≥5 AUDIT-C) and brand identification in all respondents (8 pictures with brand names removed). Results: Over one-in-ten respondents (13.2%) had participated with at least one form of marketing on social media or participated with user-created promotion (12.2%). For both, participation was greater in current drinkers and those of legal purchasing age. A logistic regression found that participation with two or more forms of marketing on social media (AOR = 1.96, p < .01) and participation with user-created promotion (AOR = 3.46, p < .001) were associated with higher-risk drinking. Respondents, on average, identified 2.58 (SD = 2.12) alcohol brands. A linear regression found participation with marketing on social media was not associated with brand identification (β = 0.01, p = .42) but participation with user-created promotion was (β = 0.05, p < .001). Conclusion: Social media provides opportunities for adolescents to participate with commercial marketing and user-created promotion and this is associated with higher-risk consumption and brand identification.
| S-EPMC6636897 | biostudies-literature