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This study determines differences in language use by Twitter users who express loneliness across age groups and genders (female, male). The work tests the hypothesis that linguistic differences mirror users’ self-expression and support needs, and it argues that interventions may need to be tailored by age and gender. Findings are used to guide the design of online loneliness interventions.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/understanding-the-expression-of-loneliness-on-twitter-across-age-groups-and-genders-research-article/136840/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/understanding-the-expression-of-loneliness-on-twitter-across-age-groups-and-genders-research-article/136840.png","ImageObject",300,407,{"name":92,"@type":93},"Eliana","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-17","2026-08-22",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",11,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What is the main goal of the study?","Question",{"text":113,"@type":114},"To determine how language use differs among Twitter users who express loneliness across age groups and genders, and how these differences can guide online interventions.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"What hypotheses does the study test?",{"text":118,"@type":114},"That LDA topics and LIWC categories extracted from tweets by different groups reflect how users express themselves and capture some of their support needs.",{"name":120,"@type":111,"acceptedAnswer":121},"Which text-analysis approaches are used to study loneliness expressions on Twitter?",{"text":122,"@type":114},"The study uses Latent Dirichlet Allocation (LDA) and the Linguistic Inquiry Word Count (LIWC) dictionary to characterize language patterns.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},136840,1787394087,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":56,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":130,"read_time":144},4398048949847,"https://ap-avatar.wpscdn.com/avatar/400002536579ef2da7f?_k=1778318612642679267","PLOS ONE  \nOPEN ACCESS  \nCitation: Andy A, Sherman G, Guntuku SC (2022) Understanding the expression of loneliness on Twitter across age groups and genders. PLoS ONE 17(9): e0273636 . [https://doi.org/10.1371/journal](https://doi.org/10.1371/journal). pone.0273636  \nEditor: Mariusz Duplaga, Uniwersytet Jagiellonski w Krakowie Biblioteka Jagiellonska, POLAND  \nReceived: January 26, 2022  \nAccepted: August 11, 2022  \nPublished: September 28, 2022  \nCopyright: © 2022 Andy et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.  \nData Availability Statement: All the files are  \navailable and can be found from the link below: [https://osf.io/zpqje/](https://osf.io/zpqje/).  \nFunding: The author(s) received no funding for this work.  \nCompeting interests: The authors have declared that no competing interests exist.  \nRESEARCH ARTICLE  \nUnderstanding the expression of loneliness on Twitter across age groups and genders  \nAnietie Andy1 *, Garrick Sherman2, Sharath Chandra Guntuku2  \n1 Penn Medicine, University of Pennsylvania, Philadelphia, PA, United States of America, 2 Computer and Information Science, University of Pennsylvania, Philadelphia, PA, United States of America  \n* [Anietie.Andy@pennmedicine.upenn.edu](Anietie.Andy@pennmedicine.upenn.edu)  \nAbstract  \nSome individuals seek support around loneliness on social media forums. In this work, we aim to determine differences in the use of language by users—in different age groups and genders (female, male), who publish posts on Twitter expressing loneliness. We hypothesize that these differences in the use of language will reflect how these users express themselves and some of their support needs. Interventions may vary depending on the age and gender of an individual, hence, in order to identify high-risk individuals who express loneliness on Twitter and provide appropriate interventions for these users, it is important to understand the variations in language use by users who belong to different age groups and genders and post about loneliness on Twitter. We discuss the findings from this work and how they can help guide the design of online loneliness interventions.  \n1 Introduction  \nSome individuals turn to social media and online forums to seek support and express themselves about their health and well-being. Prior work has used language features to gain insights from data collected from these social media and online forums as it relates to, e.g.: COVID-19 [ 1, 2], cancer [3–7], substance use recovery [8, 9], healthcare facilities [ 10], patient/provider experiences in healthcare [ 11, 12], and predicting risk of cardiovascular disease [ 13] .  \nLoneliness is a public health concern; in the United States (US), it has been shown to have an effect on the mental and physical well-being of individuals [ 14–16] . Prior work which used data from social media and online forums to study loneliness focused on: (i) studying how users who seek support around loneliness by publishing posts on an online forum focused on discussions around loneliness (loneliness forum) communicate in other online forums not related to loneliness (non-loneliness forum) [ 17, 18] and (ii) understanding and characterizing individuals who express loneliness on Twitter and the responses they receive [ 15, 16, 19] . In [ 15], it was determined that posts by individuals who express loneliness on Twitter correlated with mental health predictors. [ 16] developed a categorization scheme for expressions of loneliness on social media posts. In [ 19], it was demonstrated that the online activity of users who express loneliness often on Twitter tend to be low.  \nThe analyses in prior work did not take into consideration the differences in the way individuals of different age groups and genders communicate on social media platforms. I","cbCaimaupH3NjGZ5","https://ap.wps.com/l/cbCaimaupH3NjGZ5","pdf",446719,"English","# Introduction\n## Background and prior work\n## Motivation: age and gender differences\n## Methods overview (LDA and LIWC)\n## Study hypotheses and goals","[{\"question\":\"What is the main goal of the study?\",\"answer\":\"To determine how language use differs among Twitter users who express loneliness across age groups and genders, and how these differences can guide online interventions.\"},{\"question\":\"What hypotheses does the study test?\",\"answer\":\"That LDA topics and LIWC categories extracted from tweets by different groups reflect how users express themselves and capture some of their support needs.\"},{\"question\":\"Which text-analysis approaches are used to study loneliness expressions on Twitter?\",\"answer\":\"The study uses Latent Dirichlet Allocation (LDA) and the Linguistic Inquiry Word Count (LIWC) dictionary to characterize language patterns.\"}]","Understanding the expression of loneliness on Twitter across age groups and genders - Research article | PDF",48]