This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (2410) Peer-to-Peer Support and Online Communities (636) Natural Language Processing (692) Ontologies, Classifications, and Coding (239) Infodemiology and Infoveillance (1349) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Loneliness and Social Isolation (97)

Published on in Vol 5, No 7 (2021): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28738, first published .
Studying How Individuals Who Express the Feeling of Loneliness in an Online Loneliness Forum Communicate in a Nonloneliness Forum: Observational Study

Studying How Individuals Who Express the Feeling of Loneliness in an Online Loneliness Forum Communicate in a Nonloneliness Forum: Observational Study

Studying How Individuals Who Express the Feeling of Loneliness in an Online Loneliness Forum Communicate in a Nonloneliness Forum: Observational Study

Authors of this article:

Anietie Andy1 Author Orcid Image
Article Authors Cited by (12) Tweetations (5) Metrics

    Original Paper

    Penn Medicine, Philadelphia, PA, United States

    Corresponding Author:

    Anietie Andy, PhD

    Penn Medicine

    3400 Civic Blvd

    Philadelphia, PA,

    United States

    Phone: 1 202 486 4095

    Email: andyanietie@gmail.com


    Background: Loneliness is a public health concern, and increasingly, individuals experiencing loneliness are seeking support on online forums, some of which focus on discussions around loneliness (loneliness forums). Some of these individuals may also seek support around loneliness on online forums not related to loneliness or well-being (nonloneliness forums). Hence, to design and implement appropriate and efficient online loneliness interventions, it is important to understand how individuals who express and seek support around loneliness on online loneliness forums communicate in nonloneliness forums; this could provide further insights into the support needs and concerns of these users.

    Objective: This study aims to explore how users who express the feeling of loneliness and seek support around loneliness on an online loneliness forum communicate in an online nonloneliness forum.

    Methods: A total of 2401 users who expressed loneliness in posts published on a loneliness forum on Reddit and had published posts in a nonloneliness forum were identified. Using latent Dirichlet allocation (a natural language processing algorithm); Linguistic Inquiry and Word Count (a psycholinguistic dictionary); and the word score–based language features valence, arousal, and dominance, the language use differences in posts published in the nonloneliness forum by these users compared to a control group of users who did not belong to any loneliness forum on Reddit were determined.

    Results: It was found that in posts published in the nonloneliness forum, users who expressed loneliness tend to use more words associated with the Linguistic Inquiry and Word Count categories on sadness (Cohen d=0.10) and seeking to socialize (Cohen d=0.114), and use words associated with valence (Cohen d=0.364) and dominance (Cohen d=0.117). In addition, they tend to publish posts related to latent Dirichlet allocation topics such as relationships (Cohen d=0.105) and family and friends and mental health (Cohen d=0.10).

    Conclusions: There are clear distinctions in language use in nonloneliness forum posts by users who express loneliness compared to a control group of users. These findings can help with the design and implementation of online interventions around loneliness.

    JMIR Form Res 2021;5(7):e28738

    doi:10.2196/28738

    Keywords

    loneliness; Reddit; nonloneliness; mental health; eHealth; forum; online forum; communication; natural language processing; language; linguistics 


    Loneliness is a public health challenge [1]; it affects the well-being of individuals of all age groups [2,3] and has been linked to early death [4,5], depression [6,7], and heart disease [8].

    Several prior works [1,9,10] have analyzed data from social media platforms and online forums, some of which focus on discussions around loneliness (loneliness forums) to understand the support needs of individuals who express loneliness on these platforms. These individuals may also seek support and express concerns as it relates to loneliness, such as how to develop or maintain relationships, on online forums not focused on discussions around loneliness or well-being (nonloneliness forums). To better understand the support needs of users who express loneliness on online loneliness forums and to design and implement appropriate and efficient online interventions, it is important to study how these individuals communicate in nonloneliness forums.

    Using natural language processing methods, prior works determined that the language used in posts published on social media platforms and online forums can be used to gain insights into how users communicate on these forums and the types of support they seek and express, as it relates to their health and well-being. For example, language used in posts published on Facebook was used to train a machine learning model to predict patients risk for cardiovascular disease [11]. In addition, language used on online forum posts were used to determine the support needs of users in substance use recovery forums [12], a COVID-19 online forum [13,14], and an online cancer forum [15-17]. Regarding loneliness, prior works analyzed social media data belonging to individuals who expressed loneliness; for example, Guntuku et al [1] analyzed Twitter posts from users who self-declared feeling lonely, and it was determined that the language used by these users in their Twitter posts was more associated with mental health concerns. Kivran-Swaine et al [18] determined that posts in which users expressed loneliness tended to receive more responses compared to other posts by the same users. Ruiz et al [9] showed that the more loneliness users express on social media, the less online relationships they had. Hunt et al [10] showed that there is an association between less social media use and a decrease in the feeling of loneliness and depression.

    Similar to prior works, in this study, using natural language processing methods, language used on posts published on a nonloneliness online forum are analyzed to gain insights into the support needs and concerns of individuals who express loneliness in a loneliness online forum. Potentially, information gleaned from the analyses in this study will provide further insights into the support needs and concerns of individuals expressing loneliness on online loneliness forums, thereby informing loneliness interventions.


    Data and Design

    For the analysis in this study, data from Reddit was used. Reddit is made up of more than 1 million subforums (called subreddits) [19] focused on discussions around specific topics such as depression, loneliness, and open-ended questions spanning various topics. In addition, Reddit allows members to join several of these forums; hence, it is possible to get posts published in a nonloneliness forum by users who are members of a loneliness forum. Using Google’s BigQuery [20], which is a data warehouse with publicly accessible Reddit data sets published between December 2015 and August 2019, posts from Reddit forums focused on discussions around loneliness were identified by selecting the forums that contained the word “Lonely” in its name (eg, “/r/lonelyheartbeats,” “/r/iAMlonely,” and “/r/Lonely”). It was observed that the forum /r/Lonely had more posts and members compared to the other forums, which each had less than 200 published posts during the time period in which the data was collected. Hence, for the analysis in this study, usernames of members of /r/Lonely were used; specifically, the usernames of 9956 users who had published a total of 15,012 posts on the /r/Lonely forum were selected.

    To identify the other Reddit forums in which these users belong to and tend to publish posts, using the usernames from /r/Lonely, all the forums on Reddit were searched to determine the forums in which these /r/Lonely users tend to publish posts. It was observed that the forums with the most number of these users as members are /r/AskReddit (a forum in which users seek advice and ask open-ended questions on various topics) and /r/depression (a forum focused on discussions around depression) with posts by 24% (n=2401) and 20% (n=2031), respectively, of the /r/Lonely users (N=9956) in the data set. Since the focus of this study is to determine how individuals who express loneliness on an online loneliness forum communicate in nonloneliness forums (ie, forums not focused on loneliness or well-being), for all the analysis in this study, data from /r/AskReddit by 2401 users who expressed loneliness in /r/Lonely were used. The author reviewed the posts (N=4001) published on /r/Lonely by these users and observed that these users expressed feeling lonely in their /r/Lonely posts by stating that they were feeling lonely (eg, rephrased “I am a 25 years old female and I am always lonely”), implied that they were feeling lonely (eg, rephrased “I moved to a new city and I don’t know anyone”), or sought support as it relates to loneliness (eg, rephrased “Where can I find tools online to help with loneliness?”).

    Each of the 2401 users who posted on /r/Lonely and had published posts on /r/AskReddit were matched with a control group user who had no published posts on any loneliness forum on Reddit and had published posts on /r/AskReddit between December 2015 and August 2019.

    Table 1 shows information about the data set.

    Table 1. Summary of /r/AskReddit posts published between December 2015 and August 2019 by /r/Lonely users and a control group.
    Variables/r/Lonely usersControl group
    Users, n24012401
    Posts, n25,83434,718

    In this study, the following methods were used to determine language use differences in /r/AskReddit posts by users who express loneliness compared to the control group: a topic modeling approach, a dictionary-based approach, and a word score–based approach. Cohen d, which indicates the standardized difference between means, was used to report the effect sizes. In this study, only results with Cohen d greater than or equal to a threshold (ie, 0.10) and that are significant at Bonferroni-corrected P values <.001 are reported.

    The topic modeling approach and the dictionary-based approaches were used because prior works used these approaches to gain insights from social media data about the language use differences between individuals in different genders [21] and age groups [22], and to determine the language use differences between users who express loneliness compared to a control group of users who did not express loneliness [1]. The word score–based approach was used because prior work [23] used these methods to better understand language features associated with persuasion in online forum posts and comments.

    Topic Modeling Approach

    In this section, the natural language processing topic modeling method latent Dirichlet allocation (LDA) [24] was used. LDA works by, first, splitting words in Reddit posts into single words or tokens (tokenization). Second, words that co-occur together are clustered together; the cluster of words are referred to as topics, and based on the content words associated with each topic, a label can be assigned to the topics. For example, LDA could group the words “family,” “mom,” “dad,” “daughter,” and “son” as a reference to family. LDA assumes that the topics consist of a combination of words, and each Reddit post is made up of a combination of topics. Using the Dlatk package [25], 20 LDA topics were generated from the /r/AskReddit posts associated with /r/Lonely users and the control group users; to determine the number of LDA topics, the number of topics varied between 5 and 50 topics by starting with 5 topics and incrementing by 2 topics up to 50 topics. A total of 20 topics had the most coherent topic themes when reviewed by the author. With the generated topics, using the Dlatk package [25], the topic themes that frequently occurred in the /r/AskReddit posts by /r/Lonely users when compared with the control group users were identified.

    Dictionary-Based Approach

    In this approach, language from /r/AskReddit posts associated with the /r/Lonely users and the control group users were used to determine the prevalence of Linguistic Inquiry and Word Count (LIWC) [26] dictionary word categories in posts associated with these groups of users. LIWC is a psycholinguistic dictionary made up of 73 predefined categories such as positive and negative emotions; each of these categories has a curated list of words associated with it. LIWC has been used in several prior works [1,22,27]. Using the Dlatk package [25], for each group of /r/AskReddit posts (ie, posts belonging to /r/Lonely users and the control group users), the proportion of token words associated with LIWC categories were determined.

    Word Score–Based Approach

    The word score–based features valence, arousal, and dominance have been used by prior works to study communication strategies in an online forum [23,28]. Valence indicates the measure of the positive or negative denotation of a word; for example, “enjoyable” is a high valence word and “nightmare” is a low valence word. Arousal measures the emotional intensity expressed in a word; an example of a high arousal word is “exhilarated,” and an example of a low arousal word is “siesta.” Dominance indicates the measure of the locus of control expressed in a word; for example “powerful” is a high dominance word, and “weak” is a low dominance word. Mohammad [28] provided a lexicon of human ratings for valence, arousal, and dominance for 20,000 words in English; using this lexicon, for each post in the data set, the average ratings of all content words in each of these word categories (ie, valence, arousal, and dominance) was computed.


    Topic Modeling Approach

    Table 2 shows the most significant LDA topics in /r/Askreddit posts by /r/Lonely users compared to the control group.

    Table 2. Results from latent Dirichlet allocation analysis on /r/AskReddit posts by /r/Lonely users compared to the control group users.
    LabelHighly correlated wordsCohen dMean (SD)
    Relationshipspeople, love, hate, relationship, find, can\'t, lose, meet, stop, married0.1050.038 (0.048)
    Family and friends/mental healthfamily, friends, deal, talk, experience, depression, mental, care, service, dear0.100.038 (0.053)

    Dictionary-Based Approach

    Table 3 shows the different LIWC categories in /r/AskReddit posts most associated with /r/Lonely users compared to the control group users.

    Table 3. Results from LIWC analysis on /r/AskReddit posts by /r/Lonely users compared to the control group users.
    LIWCa categoryCohen dMean (SD)
    Social processes0.1140.157 (0.08)
    Sadness0.100.083 (0.042)

    aLIWC: Linguistic Inquiry and Word Count.

    Word Score–Based Approach

    Using Cohen d, the effect size between the features that represent the average valence, arousal, and dominance scores for posts in the data set and a feature that represents if a /r/AskReddit post was by a /r/Lonely user or a control group user was determined, as shown in Table 4.

    Table 4. Results from word score–based language feature analysis on /r/AskReddit posts by /r/Lonely users compared to the control group users.
    AttributeCohen d
    Valence0.364
    Arousal–0.004
    Dominance0.117

    Findings

    Using natural language processing methods, this study shows the distinction in language use in posts published on a nonloneliness forum by users who express and seek support around loneliness in an online loneliness forum compared to a control group of users. These language use differences reflect the support needs and concerns of these users. The findings from this study are summarized in this section.

    This study determined that users who express the feeling of loneliness in /r/Lonely tend to seek advice and ask questions about relationships on /r/AskReddit (Table 2) compared to the control group users. This finding is in line with prior work [1] that determined that individuals who expressed loneliness on Twitter tend to publish Twitter messages related to themes about difficult interpersonal relationships.

    In addition, this study has findings that were not in prior work; specifically, it was observed that individuals who express loneliness in a loneliness forum tend to seek advice and ask questions about mental health concerns as it relates to their family members and friends; for example, the following are examples of /r/AskReddit posts (rephrased) by /r/Lonely users seeking advice as it relates to their relationships with family members and friends:

    I need advice on how to deal with a family member / friend who keeps criticizing me.
    I need help, if one is struggling with mental health, what is the best way to explain it to family members and friends?

    Using LIWC, it was observed that users who expressed loneliness in the loneliness forum tended to use more words associated with sadness and wanting to socialize in the nonloneliness forum.

    Using the word score–based language features valence, arousal, and dominance, it was determined that the average valence and dominance scores in /r/AskReddit posts are more associated with posts by users who express loneliness on /r/Lonely. A potential explanation for dominance being more associated with /r/AskReddit posts by /r/Lonely users is that some of these users seek support and express vulnerability in these posts; low dominance words suggest vulnerability, hence the association. Additionally, a potential explanation for valence being more associated with /r/AskReddit posts by /r/Lonely users is that these users tend to use low valence words in these posts, hence the association.

    This study shows that users who express loneliness in a loneliness forum seek support and communicate differently from a control group of users in a nonloneliness forum. The findings from this study can aid in the design and implementation of online loneliness interventions; for example, given that users who express loneliness in the loneliness forum ask questions and seek advice as it relates to their relationships (with family and friends) and use more words associated with seeking to socialize and sadness (Table 3), online loneliness interventions can provide services in which advice and tips are given to users on how to develop, maintain, and navigate relationships.

    From this study’s findings, when designing and implementing online loneliness interventions, it is important to not only focus on user communication in loneliness forums but also look into how these users communicate in nonloneliness forums.

    Limitations

    In this study, data from Reddit users was used and may not be representative of all individuals (some of whom may not publish posts on online forums expressing their feeling of loneliness) who feel lonely.

    Ethics and Privacy

    The data set used for this study is publicly available. For all the analyses in this study, no user or moderator of any loneliness forum on Reddit (including /r/Lonely) was contacted. In addition, besides the usernames of /r/Lonely users, no other information from user profiles was used or accessed.

    Conclusion

    In this study, using natural language processing methods, it was determined that users who express loneliness in an online loneliness forum communicated differently in a nonloneliness forum when compared to a control group of users. The findings from this study can aid with the design and implementation of online loneliness interventions.

    Conflicts of Interest

    None declared.

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    ‎
    LDA: latent Dirichlet allocation
    LIWC: Linguistic Inquiry and Word Count

    Edited by G Eysenbach; submitted 12.03.21; peer-reviewed by C Entwistle, M Fiordelli; comments to author 10.05.21; revised version received 04.06.21; accepted 17.06.21; published 20.07.21

    Copyright

    ©Anietie Andy. Originally published in JMIR Formative Research (https://formative.jmir.org), 20.07.2021.

    This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included.