Facebook, Twitter, and Instagram: Simultaneously examining the association between three social networking sites and relationship stress and satisfaction.

Delle, Faith A.; Clayton, Russell B.; Jackson, Felecia F. Jordan; Lee, Jaejin

doi:10.1037/ppm0000415

Cited by 3 publications

(1 citation statement)

References 33 publications

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“…For example, Halpern et al (2017) found that jealousy indirectly predicted poorer romantic relationship quality through social media photo-related conflicts. Delle et al (2022) found that active use of Twitter and Instagram was negatively associated with relationship satisfaction through romantic relationship stress among adults aged 18–46. Few have studied the impact of jealousy on friendship quality (exception Parker et al, 2016 ).…”

Section: Studymentioning

confidence: 96%

Social Media Friendship Jealousy

Vaillancourt,

Brittain,

Eriksson

et al. 2024

Evol Psychol

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A new measure to assess friendship jealousy in the context of social media was developed. This one-factor, seven-item measure was psychometrically sound, showing evidence of validity and reliability in three samples of North American adults (Study 1, n = 491; Study 2, n = 494; Study 3, n = 415) and one-, two-, and three-year stability (Study 3). Women reported more social media friendship jealousy than men (Studies 2 and 3) and younger women had the highest levels of social media friendship jealousy (compared with younger men and older men and women; Study 2). Social media friendship jealousy was associated with lower friendship quality (Study 1) and higher social media use and trait jealousy (Study 2). The relation between social media friendship jealousy and internalizing symptoms indicated positive within time associations and longitudinal bidirectional relations (Study 3). Specifically, social media friendship jealousy predicted increases in internalizing problems, and internalizing problems predicted greater social media friendship jealousy accounting for gender and trait levels of social media friendship jealousy and internalizing problems. Anxious and depressed adults may be predisposed to monitor threats to their friendships via social media and experience negative consequences because of this behavior. Although social media interactions can be associated with positive well-being and social connectedness, our results highlight that they can also undermine friendships and mental health due to jealousy.

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Section: Studymentioning

confidence: 96%

Social Media Friendship Jealousy

Vaillancourt,

Brittain,

Eriksson

et al. 2024

Evol Psychol

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Statin Twitter: Human and Automated Bot Contributions, 2010 to 2022

Slavin,

Berman,

Beam

et al. 2024

JAHA

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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). Methods and Results We analyzed original tweets with statin‐related terms from 2010 to 2022 using a machine learning–derived classifier to determine the author's bot probability, natural language processing to assign each tweet a negative or positive sentiment, and manual qualitative analysis to identify statin skepticism in a random sample of all tweets and in highly influential tweets. We identified 1 155 735 original statin‐related tweets. Bots produced 333 689 (28.9%), humans produced 699 876 (60.6%), and intermediate probability accounts produced 104 966 (9.1%). Over time, the proportion of bot tweets decreased from 47.8% to 11.3%, and human tweets increased from 43.6% to 79.8%. The proportion of negative‐sentiment tweets increased from 27.8% to 43.4% for bots and 30.9% to 38.4% for humans. Manually coded statin skepticism increased from 8.0% to 19.0% for bots and from 26.0% to 40.0% for humans. Conclusions Over the past decade, humans have overtaken bots as generators of statin‐related content on Twitter. Negative sentiment and statin skepticism have increased across all user types. Twitter may be an important forum to combat statin‐related misinformation.

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User Analytics in Online Social Networks: Evolving from Social Instances to Social Individuals

et al. 2022

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In our era of big data and information overload, content consumers utilise a variety of sources to meet their data and informational needs for the purpose of acquiring an in-depth perspective on a subject, as each source is focused on specific aspects. The same principle applies to the online social networks (OSNs), as usually, the end-users maintain accounts in multiple OSNs so as to acquire a complete social networking experience, since each OSN has a different philosophy in terms of its services, content, and interaction. Contrary to the current literature, we examine the users’ behavioural and disseminated content patterns under the assumption that accounts maintained by users in multiple OSNs are not regarded as distinct accounts, but rather as the same individual with multiple social instances. Our social analysis, enriched with information about the users’ social influences, revealed behavioural patterns depending on the examined OSN, its social entities, and the users’ exerted influence. Finally, we ranked the examined OSNs based on three types of social characteristics, revealing correlations between the users’ behavioural and content patterns, social influences, social entities, and the OSNs themselves.

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Facebook, Twitter, and Instagram: Simultaneously examining the association between three social networking sites and relationship stress and satisfaction.

Cited by 3 publications

References 33 publications

Social Media Friendship Jealousy

Social Media Friendship Jealousy

Statin Twitter: Human and Automated Bot Contributions, 2010 to 2022

User Analytics in Online Social Networks: Evolving from Social Instances to Social Individuals

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