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Social Networks, Social Support, and...

Chen, Hui.

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Social Networks, Social Support, and Information Disclosure on Social Media for Illness.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Social Networks, Social Support, and Information Disclosure on Social Media for Illness./
作者:	Chen, Hui.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:	138 p.
附註:	Source: Dissertations Abstracts International, Volume: 82-03, Section: A.
Contained By:	Dissertations Abstracts International82-03A.
標題:	Sociology. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28087752
ISBN:	9798672151403

Social Networks, Social Support, and Information Disclosure on Social Media for Illness.
Chen, Hui.

Social Networks, Social Support, and Information Disclosure on Social Media for Illness. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 138 p.

Source: Dissertations Abstracts International, Volume: 82-03, Section: A.

Thesis (Ph.D.)--Indiana University, 2020.

This item must not be sold to any third party vendors.

People have increasingly used social media for coping with illness, such as finding health information, seeking support, and connecting with others. Social support and social network theories suggest that social media extends people's traditional offline support networks. Patients who cannot receive adequate support from their families and friends can turn to a larger network of individuals with similar experiences and health conditions. Additionally, computer-mediated communication literature argues that the anonymity of social media allows people who are reluctant to seek support in face-to-face settings to self-disclose in online settings. Stigmatized individuals feel more comfortable and secure to voice their thoughts and seek support on social media. This dissertation focuses on the aspects of social relationships, social support, and information disclosure on social media for illness. It aims to test hypotheses motivated from the theorizing about (1) social relationships and health, and (2) anonymity and self-disclosure. I conduct three empirical studies to address these two themes.Chapters 4 and 5 examine the relationship between users' online network structure and participation at the individual and group levels respectively. Chapter 4 tests hypotheses that users' network structure is associated with posting activity and sentiment. Using data from Twitter, I find that users who are more advantaged in network structure (e.g., degree, density) are more active in posting behaviors (e.g., posting volume). But no significant associations are found between network structure and posting sentiment. Chapter 5 tests hypotheses that groups' network structure is associated with group retention. Using data from an online health forum, I find that denser, closer and smaller networks have higher retention rates. Chapter 6 examines the relationship among anonymity, stigma, and self-disclosure. Using Twitter data, I assess hypotheses that anonymous patients are more likely to self-disclose. For anonymous users (compared with identifiable users), the more stigmatized their illness is, the more they self-disclose. I find a significant association between anonymity and health-related posts among cancer users, but not among depression users. Contradictory to my hypotheses, among anonymous users, cancer users (i.e., less stigmatized) are more likely to produce content related to support or health than depression users (i.e., more stigmatized).

ISBN: 9798672151403Subjects--Topical Terms:

516174
Sociology.
Subjects--Index Terms:

Social media

Social Networks, Social Support, and Information Disclosure on Social Media for Illness.
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520 $a People have increasingly used social media for coping with illness, such as finding health information, seeking support, and connecting with others. Social support and social network theories suggest that social media extends people's traditional offline support networks. Patients who cannot receive adequate support from their families and friends can turn to a larger network of individuals with similar experiences and health conditions. Additionally, computer-mediated communication literature argues that the anonymity of social media allows people who are reluctant to seek support in face-to-face settings to self-disclose in online settings. Stigmatized individuals feel more comfortable and secure to voice their thoughts and seek support on social media. This dissertation focuses on the aspects of social relationships, social support, and information disclosure on social media for illness. It aims to test hypotheses motivated from the theorizing about (1) social relationships and health, and (2) anonymity and self-disclosure. I conduct three empirical studies to address these two themes.Chapters 4 and 5 examine the relationship between users' online network structure and participation at the individual and group levels respectively. Chapter 4 tests hypotheses that users' network structure is associated with posting activity and sentiment. Using data from Twitter, I find that users who are more advantaged in network structure (e.g., degree, density) are more active in posting behaviors (e.g., posting volume). But no significant associations are found between network structure and posting sentiment. Chapter 5 tests hypotheses that groups' network structure is associated with group retention. Using data from an online health forum, I find that denser, closer and smaller networks have higher retention rates. Chapter 6 examines the relationship among anonymity, stigma, and self-disclosure. Using Twitter data, I assess hypotheses that anonymous patients are more likely to self-disclose. For anonymous users (compared with identifiable users), the more stigmatized their illness is, the more they self-disclose. I find a significant association between anonymity and health-related posts among cancer users, but not among depression users. Contradictory to my hypotheses, among anonymous users, cancer users (i.e., less stigmatized) are more likely to produce content related to support or health than depression users (i.e., more stigmatized).
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