Zheng Gao
Patrick C. Shih
ABSTRACT
Analysis of social support in online forums for people living with HIV has been relying, for the most part, on self-report instrumentation and manual coding of data. Our study applies a fully automated data analysis method based on clustering and network embedding of the largest online support forum (POZ forum)for people living with HIV. Results show that there are three sub communities of members within the forum differing in terms of member engagement, topics discussed, and types of support exchanged. This paper analyses the similarities and differences among these communities as a way to identify members that comprise each community and how they exchange support. The result can be generalized to show current situation of HIV discussion online and how social supports change in different group of people related to HIV. Therefore, better social support plans can be applied to help HIV patients relief their pain.
- Magdalena Berger, Todd H Wagner, and Laurence C Baker. 2005. Internet use and stigmatized illness. Social science & medicine 61, 8 (2005), 1821--1827.Google Scholar
- Troix Bettencourt, Antigone Hodgins, GJ Huba, and Gilbert Pickett. 1998. Bay Area Young Positives: a model of a youth-based approach to HIV/AIDS services. Journal of Adolescent Health 23, 2 (1998), 28--36.Google ScholarCross Ref
- Walter O Bockting, Michael H Miner, Rebecca E Swinburne Romine, Autumn Hamilton, and Eli Coleman. 2013. Stigma, mental health, and resilience in an online sample of the US transgender population. American journal of public health 103, 5 (2013), 943--951.Google Scholar
- Brant R Burleson. 2003. The experience and effects of emotional support: What the study of cultural and gender differences can tell us about close relationships, emotion, and interpersonal communication. Personal Relationships 10, 1 (2003), 1--23.Google ScholarCross Ref
- Constantinos K Coursaris and Ming Liu. 2009. An analysis of social support exchanges in online HIV/AIDS self-help groups. Computers in Human Behavior 25, 4 (2009), 911--918. Google ScholarDigital Library
- Kathryn P Davison, James W Pennebaker, and Sally S Dickerson. 2000. Who talks? The social psychology of illness support groups. American Psychologist 55, 2 (2000), 205.Google ScholarCross Ref
- Bo Feng and Erina L MacGeorge. 2010. The influences of message and source factors on advice outcomes. Communication Research 37, 4 (2010), 553--575.Google ScholarCross Ref
- Centers for Disease Control, Prevention, and others. 2016. Fact sheet: trends in US HIV diagnoses, 2005--2014. February 2016. (2016).Google Scholar
- Susannah Fox. 2014. The social life of health information, 2014. Pew Internet & American Life Project Washington, DC.Google Scholar
- Zheng Gao, Gang Fu, Chunping Ouyang, Satoshi Tsutsui, Xiaozhong Liu, and Ying Ding. 2018. edge2vec: Learning Node Representation Using Edge Semantics. arXiv preprint arXiv:1809.02269 (2018).Google Scholar
- Zheng Gao and Xiaozhong Liu. 2017. Personalized community detection in scholarly network. iConference 2017 Proceedings Vol. 2 (2017).Google Scholar
- Aditya Grover and Jure Leskovec. 2016. node2vec: Scalable feature learning for networks. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 855--864. Google ScholarDigital Library
- Eunkyung Kim, Jeong Yeob Han, Tae Joon Moon, Bret Shaw, Dhavan V Shah, Fiona M McTavish, and David H Gustafson. 2012. The process and effect of supportive message expression and reception in online breast cancer support groups. Psycho-Oncology 21, 5 (2012), 531--540.Google ScholarCross Ref
- Aideen Lawlor and Jurek Kirakowski. 2014. Online support groups for mental health: A space for challenging self-stigma or a means of social avoidance? Computers in Human Behavior 32 (2014), 152--161.Google ScholarDigital Library
- Li Li, Sheng Wu, Zunyou Wu, Stephanie Sun, Haixia Cui, and Manhong Jia. 2006. Understanding family support for people living with HIV/AIDS in Yunnan, China. AIDS and Behavior 10, 5 (2006), 509--517.Google ScholarCross Ref
- Xiaozhong Liu, Xing Yu, Zheng Gao, Tian Xia, and Johan Bollen. 2016. Comparing community-based information adoption and diffusion across different microblogging sites. In Proceedings of the 27th ACM Conference on Hypertext and Social Media. ACM, 103--112. Google ScholarDigital Library
- Yan Liu, Rachel Kornfield, Bret R Shaw, Dhavan V Shah, Fiona McTavish, and David H Gustafson. 2017. When support is needed: Social support solicitation and provision in an online alcohol use disorder forum. DIGITAL HEALTH 3 (2017), 2055207617704274.Google ScholarCross Ref
- Juan Maestre, Susan Herring, Aehong Min, Ciabhan Connelly, and Patrick Shih. 2018a. Where and How to Look for Help Matters: Analysis of Support Exchange in Online Health Communities for People Living with HIV. Information 9, 10 (2018), 259.Google ScholarCross Ref
- Juan F Maestre, Haley MacLeod, Ciabhan L Connelly, Julia C Dunbar, Jordan Beck, Katie A Siek, and Patrick C Shih. 2018b. Defining through expansion: conducting asynchronous remote communities (arc) research with stigmatized groups. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. ACM, 557. Google ScholarDigital Library
- Kathy McKeown, Hal Daume, Snigdha Chaturvedi, John Paparrizos, Kapil Thadani, Pablo Barrio, Or Biran, Suvarna Bothe, Michael Collins, Kenneth R Fleischmann, and others. 2016. Predicting the impact of scientific concepts using full-text features. Journal of the Association for Information Science and Technology 67, 11 (2016), 2684--2696. Google ScholarDigital Library
- Phoenix KH Mo and Neil S Coulson. 2010. Empowering processes in online support groups among people living with HIV/AIDS: A comparative analysis of âĂŸlurkersâĂŹ and âĂŸpostersâĂŹ. Computers in Human Behavior 26, 5 (2010), 1183--1193. Google ScholarDigital Library
- Daniel Müllner. 2011. Modern hierarchical, agglomerative clustering algorithms. arXiv preprint arXiv:1109.2378 (2011).Google Scholar
- Hyun Jung Oh, Elif Ozkaya, and Robert LaRose. 2014. How does online social networking enhance life satisfaction? The relationships among online supportive interaction, affect, perceived social support, sense of community, and life satisfaction. Computers in Human Behavior 30 (2014), 69--78. Google ScholarDigital Library
- Stephen A Rains. 2014. The implications of stigma and anonymity for self-disclosure in health blogs. Health communication 29, 1 (2014), 23--31.Google Scholar
- Stephen A Rains, Emily B Peterson, and Kevin B Wright. 2015. Communicating social support in computer-mediated contexts: A meta-analytic review of content analyses examining support messages shared online among individuals coping with illness. Communication Monographs 82, 4 (2015), 403--430.Google ScholarCross Ref
- Patricia M Reeves. 2000. Coping in cyberspace: the impact of Internet use on the ability of HIV-positive individuals to deal with their illness. Journal of Health communication 5, sup1 (2000), 47--59.Google Scholar
- James D Robinson and Jeanine Turner. 2003. Impersonal, interpersonal, and hyperpersonal social support: Cancer and older adults. Health communication 15, 2 (2003), 227--234.Google Scholar
- Gerard Salton, Anita Wong, and Chung-Shu Yang. 1975. A vector space model for automatic indexing. Commun. ACM 18, 11 (1975), 613--620. Google ScholarDigital Library
- Irwin G Sarason, Barbara R Sarason, and Brant R Burleson. 2009. Understanding the outcomes of supportive communication: A dual-process approach. Journal of Social and Personal Relationships 26, 1 (2009), 21--38.Google ScholarCross Ref
- Santiago Segarra, Mark Eisen, and Alejandro Ribeiro. 2013. Authorship attribution using function words adjacency networks. In Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on. IEEE, 5563--5567.Google Scholar
- Karen Sparck Jones. 1972. A statistical interpretation of term specificity and its application in retrieval. Journal of documentation 28, 1 (1972), 11--21.Google ScholarCross Ref
- Jennifer G Tichon and Margaret Shapiro. 2003. The process of sharing social support in cyberspace. CyberPsychology & Behavior 6, 2 (2003), 161--170.Google ScholarCross Ref
- Kristina Toutanova, Dan Klein, Christopher D Manning, and Yoram Singer. 2003. Feature-rich part-of-speech tagging with a cyclic dependency network. In Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology-Volume 1. Association for Computational Linguistics, 173--180. Google ScholarDigital Library
- Agnes Vayreda and Charles Antaki. 2009. Social support and unsolicited advice in a bipolar disorder online forum. Qualitative health research 19, 7 (2009), 931--942.Google Scholar
- Joseph B Walther and Shawn Boyd. 2002. Attraction to computer-mediated social support. Communication technology and society: Audience adoption and uses 153188 (2002).Google Scholar
- Xiao Wang, Peng Cui, Jing Wang, Jian Pei, Wenwu Zhu, and Shiqiang Yang. 2017. Community Preserving Network Embedding. (2017).Google Scholar
- Marsha White and Steve M Dorman. 2001. Receiving social support online: implications for health education. Health education research 16, 6 (2001), 693--707.Google Scholar
- Kevin B Wright, Sally B Bell, Kevin B Wright, and Sally B Bell. 2003. Health-related support groups on the Internet: Linking empirical findings to social support and computer-mediated communication theory. Journal of Health Psychology 8, 1 (2003), 39--54.Google ScholarCross Ref
- Tian Xia, Xing Yu, Zheng Gao, Yijun Gu, and Xiaozhong Liu. 2017. Internal/External information access and information diffusion in social media. iConference 2017 Proceedings Vol. 2 (2017).Google Scholar
- Chenwei Zhang, Zheng Gao, and Xiaozhong Liu. 2016. How others affect your Twitter# hashtag adoption? Examination of community-based and context-based information diffusion in Twitter. IConference 2016 Proceedings (2016).Google ScholarCross Ref
- Kang Zhao, John Yen, Greta Greer, Baojun Qiu, Prasenjit Mitra, and Kenneth Portier. 2014. Finding influential users of online health communities: a new metric based on sentiment influence. Journal of the American Medical Informatics Association 21, e2 (2014), e212--e218.Google ScholarCross Ref
Recommendations
Commitment of Newcomers and Old-timers to Online Health Support Communities
CHI '17: Proceedings of the 2017 CHI Conference on Human Factors in Computing SystemsFor online communities to be successful, they must retain an adequate number of members who contribute to the community. The amount and type of communication members receive can play an important role in generating and sustaining members' commitment to ...
Knowledge Sharing and Community Promotion in Online Health Communities: Examining the Relationship Between Social Support, Community Commitment, and Trust Transfer
Social Computing and Social Media. Participation, User Experience, Consumer Experience, and Applications of Social ComputingAbstractOnline health communities (OHCs) have now become a valuable platform for people to seek health-related information. Knowledge sharing and community promotion in the OHCs are critical to sustain their continuous use and improve their engagement. ...
Personas in online health communities
Display Omitted We show Caretakers, Scientists, Adventurers, and Opportunists as personas in OHCs.We present social quality and quantity metrics practitioners can use to detect these personas.These personas help improve retention in online social health ...
Comments