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| Title: | 探討網路社群參與者的情緒表達與資訊搜尋行為 - 以 YouTube 育兒社群為研究個案
Online Community Participants’ Emotion and Information Seeking Behaviour: A YouTube-based Parenting Communit |
| Authors: | 林家瑜
Lin, Chia-Yu |
| Contributors: | 李怡慧
Lee, Yi-Hui
林家瑜
Lin, Chia-Yu |
| Keywords: | 線上社群
社會支持
情緒
資訊搜尋行為
語意分析
社會網絡分析
Online community
Social support
Emotions
Information seeking behaviour
Sentiment analysis
Social network analysis |
| Date: | 2023 |
| Issue Date: | 2023-08-02 14:05:32 (UTC+8) |
| Abstract: | 現有學術研究對線上社群的社會支持有諸多的討論，其中又以情感支持及資訊支持最為廣泛及重要。然而，若線上社群只有單一提供情感的抒發或知識，則無法促成現今線上社群的重要性與效益。因此，本研究認為有其必要進一步探究，線上社群參與者所尋求的情感支持與資訊支持如何交織，以促成社會支持。具體來說，在參與者是如何在社群中表露情緒，同時尋求資訊。本研究以一個 YouTube線上育兒社群為例，探討父母所表露的五種情緒–愛、悲傷、恐懼、生氣及倦怠，及兩種資訊搜尋行為–明確的資訊搜尋行為及有意識的資訊搜尋行為是否相關，若是，又如何相關。本研究從 YouTube 影片下方蒐集了 13,071 筆留言，使用卡方檢定檢視留言中情緒與資訊搜尋行為的關係，其中透過語意分析將留言分類為五種情緒及兩種資訊搜尋行為。同時，本研究使用社會網絡分析呈現情緒字詞與資訊主題之間的關聯，來呈現父母尋求的資訊以及伴隨的情緒。更區分在情緒張力較大的 COVID-19 主題下，父母的情緒與資訊搜尋行為之間的關係是否改變。本研究有三個主要發現，第一，情緒與資訊搜尋行為呈現顯著相關，且父母最常在線上社群中表露的情緒是恐懼，伴隨著明確的資訊搜尋行為。第二，從社會網絡分析的結果發現，當父母表達恐懼的感受時，往往一併尋求COVID-19、基本症狀，以及疾病相關的資訊。最後，父母在經歷社會氛圍較為緊張的COVID-19事件下，他們所表達的情緒與資訊搜尋行為也呈現顯著的關聯。在學術貢獻上，本研究澄清了情緒與資訊搜尋行為之間的關係，且對不同的情緒在兩種資訊搜尋行為上的展現有更深入的認識。在實務貢獻上，本研究綜合了文獻、LIWC工具及本研究的人工文本分析，整理出父母五種情緒的情緒詞典，有助於日後情緒詞典的研究。本研究也提供社群經營者及父母更加瞭解育兒時主要尋求的資訊及伴隨的情緒。
The importance of online communities (OCs) in providing participants’ emotional support and health knowledge has been evident in the literature. However, the question how such emotional support and information support intertwine to
contribute the emergence of social support in OCs remains unclear. To fulfill the research gap, the study investigated the relations between emotion and information seeking behaviour (ISB) in an open communal context. To do so, the researcher analysed 13,071 posts in a YouTube-based parenthood OC by conducting semantic analysis. Five forms of emotions (i.e., love, sadness, fear, anger, and burnout) that parents often experienced were examined. Two types of ISB, i.e., formalised and conscious, were investigated in relation to these emotions. This study used chi-square test to examine the relations between emotions and ISB. To gain an in-depth understanding for how emotions and ISBs were exactly expressed, sentiment analysis was adopted. Further, social network analysis was conducted to reveal the relationship between emotional expressions and information topics. In addition, this study explored whether the relation between emotion and ISB was different under the intense emotional context, i.e., COVID-19 theme. This study revealed three findings. First, there was significant relation between emotion and ISB. “Fear” is the most common emotions expressed by parents in this OC, accompanied by formalised ISB. Second, parents often experience fear when seeking information on COVID-19, basic symptoms, and sever diseases. Third, under the intense emotional context of the COVID-19 pandemic, there was a significant relationship between emotion and ISB. This study made both theoretical and practical contributions. First, this study clarified the relation between emotion and ISB, and further explored the different types of ISBs across five emotions. With regard to the practical contributions, this study suggested OC practitioners with a better understanding of the information and emotions that are most sought after and expressed when parents face parenting challenges so that they can provide even better service to the public. |
| Reference: | AbuSa’aleek, A. O. (2015). Internet linguistics: A linguistic analysis of electronic discourse as a new variety of language. International Journal of English Linguistics, 5(1), 135-145.
Aslam, F., Awan, T. M., Syed, J. H., Kashif, A., and Parveen, M. (2020). Sentiments and emotions evoked by news headlines of coronavirus disease (COVID-19) outbreak. Humanities and Social Science Communications, 7(1), 1-9.
Chen, L, Baird, A., and Straub, D. (2019). Fostering participant health knowledge and attitudes: An econometric study of a chronic disease-focused online health community. Journal of Management Information Systems, 36(1), 194-229.
Choi, E., Kitzie, V., and Shah, C. (2013). A machine learning-based approach to predicting success of questions on social question-answering. iConference 2013 Proceedings, (pp. 409-421).
Chua, A. Y. K. and Banerjee, S. (2015). Answers or no answers: Studying question answerability in Stack Overflow. Journal of Information Science, 41(5), 720-731.
Cobb, S. (1976). Social support as a moderator of life stress. Psychosomatic Medicine, 38(5), 300-314.
Cohen, J. (1960). A coefficient of agreement for normal scales. Educational and Psychological Measurement. 20(1), 37-46.
Colineau, N. and Paris, C. (2010). Talking about your health to strangers: Understanding the use of online social networks by patients. New Review of Hypermedia and Multimedia, 16(1-2), 141-160.
Coursaris, C. K. and Liu, M. (2009). An analysis of social support exchanges in online HIV/AIDS self-help groups. Computers in Human Behavior, 25(4), 911-918.
Glascoe, F. P. (1997). Parents` concerns about children`s development: Prescreening technique or screening test? Pediatrics, 99(4), 522-528.
Henderson, A. C., Sandra M. H., and Jeffrey H. (2010). A new state of surveillance? An application of Michel Foucault to modern motherhood. Surveillance & Society, 7(3/4), 231-247.
Huang, K.Y., Chengalur-Smith, I., and Pinsonneault, A. (2019). Sharing is caring: Social support provision and companionship activities in healthcare virtual support communities. MIS Quarterly, 43(2), 295-423.
Josefsson, U. (2005). Coping with illness online: The case of patients’ online communities. The Information Society, 21, 143-153.
Kearney, P. M. and Griffin, T. (2001). Between joy and sorrow: being a parent of a child with developmental disability. Journal of Advanced Nursing, 34(5), 582-592.
Keller, M. M., Frenzel, A. C., Goetz, T., Pekrun, R., and Hensley, L. (2014). Exploring teacher emotions: A literature review and an experience sampling study. In P. W. Richardson, S. A. Karabenick, and H. M. G. Watt (Eds.) (2014). Teacher Motivation: Theory and Practice (1st ed.), pp. 69-82. NY: Routledge.
Khoo, C. SG. (2018). Lexicon-based sentiment analysis: Comparative evaluation of six sentiment lexicons. Journal of Information Science, 44(4), 491-511.
Khatoon, S. and Rehman, V. (2021). Negative emotions in consumer brand relationship: A review and future research agenda. International Journal of Consumer Studies, 45, 719-749.
Krizan, Z. and Hisler, G. (2019). Sleepy anger: Restricted sleep amplifies angry feelings. Journal of Experimental Psychology: General, 148(7), 1239–1250.
Lasker, J. N., Sogolow, E. D., and Sharim, R. R. (2005). The role of an online community for people with a rare disease: Content analysis of messages posted on a primary biliary cirrhosis mailinglist. Journal of Medical Internet Research, 7(1), e10.
Lee, S. Y., and Hawkins, R. P. (2016). Worry as an uncertainty-associated emotion: Exploring the role of worry in health information seeking. Health Communication, 31(8), 926-933.
Liamputtong, P. (2006). Motherhood and “moral career”: discourses of good motherhood among southeast Asian immigrant women in Australia, Qual Sociol, 29, 25-53.
Loane, S. S. and D`Alessandro, S. (2013). Communication that changes lives: Social support within an online health community for ALS. Communication Quarterly, 61(2), 236-251.
Lupton, D. (2000). `A love/hate relationship`: The ideals and experiences of first- time mothers. Journal of Sociology, 36(1). 50-63.
Mehta, Y., Majumder, N., Gelbukh, A., and Cambria, E. (2020). Recent trends in deep learning based personality detection. Artificial Intelligence Review, 53, 2313-2339.
Michaels, P. A. and Kokanovic, R. (2018). The complex and contradictory emotional paths to parenthood. In R. Kokanović, P. A. Michaels, K. Johnston-Ataata (Eds.). (2018). Paths to Parenthood: Emotions on the journey through pregnancy, childbirth, an early parenting, pp. 1-17. Springer.
Mikolajczak, M., Brianda, M. E., Avalosse, H., and Roskam, I. (2018). Consequences of parental burnout: Its specific effect on child neglect and violence. Child Abuse & Neglect, 80, 134-145.
Mikolajczak, M., Gross, J. J., and Roskam, I. (2019). Parental burnout: What is it, and why does it matter? Clinical Psychological Science, 7(6), 1-11.
Mohammad, S. M., and Turney, P. D. (2012). Crowdsourcing a word – emotion association lexicon. Computational Intelligence, 29(3), 436-465.
Na, J. C. and Chia, S. W. (2008) Impact of online resources on informal learners: Parents’ perception of their parenting skills, Computers & Education, 51(1) 173-186.
Nurka, C. (2018). Postnatural families: Refiguring intimacy through assisted reproduction. In R. Kokanović, P. A. Michaels, K. Johnston-Ataata (Eds.). (2018). Paths to Parenthood: Emotions on the journey through pregnancy, childbirth, an early parenting, pp. 21-43. Springer.
Nyström, K. and Öhrling, K. (2004). Parenthood experiences during the child’s first year: Literature review. Journal of Advanced Nursing, 46(3), 319-330.
Ouvrein, G. (2022). Mommy influencers: helpful or harmful? The relationship between exposure to mommy influencers and perceived parental self-efficacy among mothers and primigravida. New Media & Society, 0.
Öztora, S., Arslan, A., Caylan, A., and Dağdeviren, H. N. (2019). Postpartum depression and affecting factors in primary care, Nigerian Journal of Clinical Practice, 22(1), 85-91.
Pak, A. and Paroubek, P. (2010 May). Twitter as a corpus for sentiment analysis and opinion mining. In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC`10), pp. 1320-1326. Valletta, Malta. European Language Resources Association (ELRA).
Pálsdóttir, Á. (2017). From noticing to suspecting: The initial stages in the information behaviour of informal caregivers of people with dementia. In: J. Zhou and G. Salvendy (Eds.). Human Aspects of IT for the Aged Population. Applications, Services and Contexts. ITAP 2017. Part II. 10298, p. 452-466. Springer, Cham.
Paulson, J. F. and Bazemore, S. D. (2010). Prenatal and postpartum depression in fathers and its association with paternal depression: A meta-analysis, Journal of American Medical Association, 303(19), 1961-1969.
Pennebaker, J. W., Boyd, R. L., Jordan, K., and Blackburn, K. (2015). The development and psychometric properties of LIWC2015. University of Texas-Austin.
Plutchik, R. (1982). A psychoevolutionary theory of emotions. Social Science Information, 21, 529-553.
Preece, J. (2001). Sociability and usability in online communities: Determining and measuring success. Behaviour & Information Technology, 20(5), 237-356.
Prescott, J., Rathbone, A. L., and Brown G. (2020). Online peer to peer support: qualitative analysis of UK and US open mental health Facebook groups. Digital Health, 6, 1-17.
Romano, A. M. (2007). A changing landscape: Implications of pregnant women’s internet use for childbirth educators. Journal of Perinatal Education, 16(4), 18-24.
Rotkirch, A. and Janhunen, K. (2009). Maternal guilt. Evolutionary Psychology, 8(1), 90-106.
Ruthven, I. (2019). The language of information need: Differentiating conscious and formalized information needs. Information Processing and Management, 56(1), 77-90.
Ruthven, I., Buchanan, S., and Jardine, C. (2018) Isolated, overwhelmed, and worried: Young first-time mothers asking for information and support online. Journal of the Association for Information Science and Technology, 69(9), 1073-1083.
Shaver, P., Schwartz, J., Kirson, D., and O`Connor, C. (1987). Emotion knowledge: Further exploration of a prototype approach. Journal of Personality and Social Psychology, 52(6), 1061–1086.
Shiha, M. O., and Ayvaz, S. (2017). The effects of emoji in sentiment analysis. International Journal of Computer Electrical Engineering, 9(10), 360-369.
Taboada, M., Brooke, J., Tofiloski, M., Voll, K., and Stede, M. (2011) Lexicon-based methods for sentiment analysis. Association for Computational Linguistics, 37(2), 267-307.
Tausczik, Y. R. and Pennebaker, J. W. (2010). The psychological meaning of words: LIWC and computerized text analysis methods. Journal of Language and Social Psychology, 29(1), 24-54.
Taylor, R. S. (1968). Question-negotiation and information seeking in libraries. College & Research Libraries, 29(3), 178–194.
Troiano, G. (2022 June 2). 40 statistics you should know about online communities in 2022. Amity. https://www.amity.co/blog/40-statistics-you-should-know-about-online-communities.
Turner, A. (2023 May). Reddit user base & growth statistics: How many people sse reddit? BankMyCell. https://www.bankmycell.com/blog/number-of-reddit-users/.
Vidal, L., Ares, G., and Jaeger, S. R. (2016). Use of emoticon and emoji in tweets for food-related emotional expression. Food Quality and Preference, 49, 119-128.
White, M. and Dorman, M. (2001). Receiving social support online: Implications for health education. Health Education Research, 16(6), 693-707.
Wicks, P., Massagli, M., Forst, J., Brownstein, C., Okun, S., Vaughan, T., Bradley, R., and Heywood, J. (2010). Sharing health data for better outcomes on PatientsLikeMe. Journal of Medical Internet Research, 12(2), e19.
Wiebe, J. M. (1994). Tracking point of view in narrative. Association for Computational Linguistics, 20(2), 233-287.
Yan, L. and Tan, Y. (2014). Feeling blue? Go online: An empirical study of social support among patients. Information Systems Research, 25(4), 690-709.
Yeshua-Katz, D., Rains, S. A., Peterson, E. B., and Wright, K. B. (2020). Digital stigma coping strategies: A meta-analytic review of the association between health-related stigma dimensions and social support messages shared online. The Information Society, 36(1), 19-29.
Zhang, X. and Liu, S. (2022). Understanding relationship commitment and continuous knowledge sharing in online health communities: A social exchange perspective. Journal of Knowledge Management, 26(3), 592-614.
Zhao, H., Wang, J., and Zhang, H. (2022). Influence of social support on individual health knowledge adoption in online diabetes communities: The mediating role between cognition and emotion. Aslib Journal of Information Management, 74(6), 1048-1069.
Zhao, J., Wang, T., and Fan, X. (2015). Patient value co-creation in online health communities: Social identity effects on customer knowledge contributions and membership continuance intentions in online health communities. Journal of Service Management, 26(1), 72-96.
Zhi, Y., Shu, B., Luo, L., and Wang, J. (2022). Gender and linguistic distinctions of information needs in the Chinese context: Conscious and formalized levels. Library and Information Science Research, 44, 101195. |
| Description: | 碩士
國立政治大學
資訊管理學系
110356029 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0110356029 |
| Data Type: | thesis |
| Appears in Collections: | [資訊管理學系] 學位論文
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