| 研究生: |
蘇立舜 Li-Shun Su |
|---|---|
| 論文名稱: |
#不想上班–以Hashtag分析壓力與職業倦怠的趨勢 A Study on Stress and Occupational Burnout Based on #Hashtags Analysis |
| 指導教授: | 范錚強 |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 資訊管理學系 Department of Information Management |
| 論文出版年: | 2017 |
| 畢業學年度: | 105 |
| 語文別: | 中文 |
| 論文頁數: | 49 |
| 中文關鍵詞: | Instagram 、Hashtag 、壓力 、職業倦怠 、內容分析 、集群分析 |
| 外文關鍵詞: | Instagram, Hashtag phonation, stress, occupational burnout, content analysis, cluster analysis |
| 相關次數: | 點閱:8 下載:0 |
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過去二十年來,網際網路與行動通訊網路的發展,都隨著時間有著巨大的進步。在社群網絡上,年輕族群更常選擇使用Instagram而不是Facebook。許多人在Instagram上使用Hashtag來表達自己的情感。近年來,工作壓力一直是被公眾所重視的議題。
本研究試圖探索Instagram使用者在表達負面情緒的現象,包括像Instagram上的壓力與職業倦怠。本研究採用內容分析法,分析與壓力和職業倦怠相關的Hashtag。本研究收集到5204篇有使用Hashtag的貼文,並使用SPSS進行資料分析。也利用「集群分析法」將使用者分為不同集群。
分析結果顯示:(1) 假期結束前的晚上,包括週末在內,與負面情緒相關的Hashtag達到高峰。假期後症候群 (Post-holiday syndrome),即藍色星期一 (Blue Monday) 確實存在。使用者在假期晚上結果更高,這代表這個現象是從前一天就已開始,並蔓延到隔天。(2) 在正常工作日時,中午之前的Hashtag數量是最低的。表示大多數人都正常地休息,並且不會在工作開始之前進行抱怨。(3) 工作日的下午是數量第二低的時段,這表示雖然利用行動裝置使用社群媒體十分方便,但大部分員工不會使用上班時間來接觸社群網絡。(4) 數量第二高的是工作日的晚上,表示經過一整天的辛勤工作,使用者心情疲憊,並且有時間發洩抱怨。(5) Hashtag的分析實際上可以作為反應使用者情感的方法。
The last two decades has witnessed a tremendous advance in both Internet and mobile network usage. On the social network front, younger generation more often choose to use Instagram, rather than Facebook. Many people express their emotions on Instagram using hashtags. In recent year, job stress has always been a public concern.
This study attempts to explore the phenomena of Instagram users expressing negative emotions, including stress and occupational burnout on the Instagram. A content analysis was carried out, analyzing Hashtags relating to stress and burnout. Data from 5204 post using Hashtag were collected and analyzed SPSS. The data was also cluster analyzed.
Analysis reveals that: (1) Hashtag phonation related to negative emotions peaks during the evening before closing of a holiday, including weekends. Post-holiday syndrome (i.e. Blue Monday) truly exist, and users are even bluer on holiday evenings, meaning it actually starts the night before. (2) Hashtag phonation during the wee hours and the morning (before noon) on normal work days is the lowest, indicating most people do rest normally, and do not tend to complain when they start working. (3) The afternoons of work days is the second most silent period. Together with workday morning just mentioned, these show that while the use of social networks on smartphones are convenient, employees still refrain from using employer’s time to access social networks. (4) The second highest phonation level goes to workday evenings, indicating that after a whole day of hard work, users are tired with their body and mind, bad mood surge and it is free time to express their complains. (5) Analysis of Hashtags can actually be used as an expedient way of reflecting user emotions.
英文文獻
1. Ames, M., & Naaman, M. (2007). Why we tag: motivations for annotation in mobile and
online media. In Proceedings of the SIGCHI conference on Human factors in computing
systems (pp. 971-980). ACM.
2. Andalibi, N., Ozturk, P., & Forte, A. (2017). Sensitive Self-disclosures, Responses, and
Social Support on Instagram: the case of #depression. In Proceedings of the ACM
Conference on Computer Supported Cooperative Work (CSCW 2017).
3. Benevenuto, F., Magno, G., Rodrigues, T., & Almeida, V. (2010). Detecting spammers on
twitter. In Collaboration, electronic messaging, anti-abuse and spam conference (CEAS)
(Vol. 6, p. 12).
4. Bereson, B. (1952). Content Analysis in Communications Research, New York: Free Press.
5. Blau, G. (1981). A Empirical Investigation of Job Stress, Social Support, Service Length,
and Job Strain, Organizational Behavior and Human Performance, 27(2), 279-302.
6. Bode, L., Hanna, A., Yang, J., & Shah, D. V. (2015). Candidate networks, citizen clusters,
and political expression: Strategic hashtag use in the 2010 midterms. The ANNALS of the
American Academy of Political and Social Science, 659(1), 149-165
7. Brewer, E., & McMahan, J. (2003). Job stress and burnout among industrial and technical
teacher educators. Journal of Vocational Education Research, 28(2), 125-140.
8. Burgess, J., & Bruns, A. (2012). (Not) the Twitter election: the dynamics of the #ausvotes
conversation in relation to the Australian media ecology. Journalism Practice, 6(3), 384-
402.
9. Cullum-Swan B., Manning, P. (1994). Narrative, content, and semiotic analysis. Handbook
of qualitative research, 463-477.
10. Davenport, S. W., Bergman, S. M., Bergman, J. Z., & Fearrington, M. E. (2014). Twitter versus Facebook: Exploring the role of narcissism in the motives and usage of different social media platforms. Computers in Human Behavior, 32, 212-220.
11. Davidov, D., Tsur, O., & Rappoport, A. (2010). Enhanced sentiment learning using twitter
hashtags and smileys. In Proceedings of the 23rd international conference on
computational linguistics: posters (pp. 241-249). Association for Computational
Linguistics.
12. Davidov, D., Tsur, O., & Rappoport, A. (2010). Semi-supervised recognition of sarcastic
sentences in twitter and amazon. In Proceedings of the fourteenth conference on
computational natural language learning (pp.107-116). Association for Computational
Linguistics.
13. Derlega, V. J., & Margulis, S. T. (1983). Loneliness and intimate communication. Social
psychology, 207-226.
14. Dumbrell, D., & Steele, R. (2015, January). #worldhealthday 2014: The Anatomy of a
Global Public Health Twitter Campaign. In System Sciences (HICSS), 2015 48th Hawaii
International Conference on (pp. 3094-3103). IEEE.
15. Etzion, D. (1984). Moderating effect of social support on the stress–burnout relationship.
Journal of applied psychology, 69(4), 615.
16. Ferrara, E., Interdonato, R., & Tagarelli, A. (2014). Online popularity and topical interests
through the lens of instagram. In Proceedings of the 25th ACM conference on Hypertext
and social media (pp. 24-34). ACM.
17. Freudenberger, H. J. (1974). Staff burnout. Journal of Social Issues, 30, 159-165.
18. Freudenberger, H. J. (1980). Burnout: The high cost of high achievement. New York:
Anchor Press.
19. Guidry, J. D., Messner, M., Jin, Y., & Medina-Messner, V. (2015). From #mcdonaldsfail
to #dominossucks: An analysis of Instagram images about the 10 largest fast food
companies. Corporate Communications: An International Journal, 20(3), 344-359.
20. Kim, M., Kim, B., Kim, H., Baek, S., Shin, H., Lee, I., & Kim, J. (2016). The Effect of Emotion Sharing with Hashtag on Perceived Attention Seeking and Social Interactivity. In Proceedings of HCI Korea (pp. 460-467).
21. Kong, S., Mei, Q., Feng, L., Ye, F., & Zhao, Z. (2014, July). Predicting bursts and
popularity of hashtags in real-time. In Proceedings of the 37th international ACM SIGIR
conference on Research & development in information retrieval (pp. 927-930). ACM.
22. Ma, Z., Sun, A., & Cong, G. (2013). On predicting the popularity of newly emerging
hashtags in twitter. Journal of the American Society for Information Science and
Technology, 64(7), 1399-1410.
23. Maslach, C. (1976). Burned-out. Human Behavior, 5, 16-22.
24. Maslach, C. (2003). Burnout: The cost of caring. ISHK.
25. Mearns, J., & Cain, J. E. (2003). Relationships between teachers' occupational stress and
their burnout and distress: Roles of coping and negative mood regulation expectancies.
Anxiety, Stress & Coping, 16(1), 71-82.
26. Mishori, R., Levy, B., & Donvan, B. (2014). Twitter Use at a Family Medicine Conference.
Family medicine, 46(8), 608-14.
27. Nov, O., & Ye, C. (2010). Why do people tag? motivations for photo tagging.
Communications of the ACM, 53(7), 128-131.
28. Oh, C., Lee, T., Kim, Y., Park, S., & Suh, B. (2016, May). Understanding Participatory
Hashtag Practices on Instagram: A Case Study of Weekend Hashtag Project. In
Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in
Computing Systems (pp. 1280-1287). ACM.
29. Ohtsu, T., Kokaze, A., Osaki, Y., Kaneita, Y., Shirasawa, T., Ito, T., & Ohida, T. (2009).
Blue Monday phenomenon among men: suicide deaths in Japan. Acta Medica Okayama,
63(5), 231-236.
30. Parker, D. F., & DeCotiis, T. A. (1983). Organizational determinants of job stress.
Organizational behavior and human performance, 32(2), 160-177.
31. Robbins, S . P. (1993). Organizational behavior: Concepts, controversies, and application
(6th ed.). New York: Prentice-Hall.
32. Schuler, R. S. (1980). Definition and conceptualization of stress in organizations.
Organizational behavior and human performance, 25(2), 184-215.
33. Selye, H. (1956). The stress of life. New York: McGraw-Hill.
34. Sheldon, P., & Bryant, K. (2016). Instagram: Motives for its use and relationship to narcissism and contextual age. Computers in Human Behavior, 58, 89-97.
35. Small, T. A. (2011). What the hashtag? A content analysis of Canadian politics on Twitter.
Information, Communication & Society, 14(6), 872-895.
36. Smith, C. (1993). The measurement properties of the role conflict and role ambiguity
scales: A review and extension of the empirical research. Journal of Organizational
Behavior, 14, 37-48.
37. Stone, A. A., Hedges, S. M., Neale, J. M., & Satin, M. S. (1985). Prospective and cross-
sectional mood reports offer no evidence of a" blue Monday" phenomenon. Journal of
Personality and Social Psychology, 49(1), 129.
38. Strohmaier, M., Körner, C., & Kern, R. (2010). Why do Users Tag? Detecting Users'
Motivation for Tagging in Social Tagging Systems. In ICWSM.
39. Wang, W., Hernandez, I., Newman, D. A., He, J., & Bian, J. (2016). Twitter analysis:
studying US weekly trends in work stress and emotion. Applied Psychology, 65(2), 355-
378.
40. Weber, K., & Roehl, W. S. (1999). Profiling people searching for and purchasing travel
products on the World Wide Web. Journal of travel research, 37(3), 291-298.
41. Weiten, W. (2008). Psychology: Themes and variations: Themes and variations. Cengage
Learning.
42. Xiao, F., Noro, T., & Tokuda, T. (2012). News-Topic oriented hashtag recommendation in
twitter based on characteristic co-occurrence word detection. In International Conference
on Web Engineering (pp. 16-30). Springer Berlin Heidelberg.
43. Zappavigna, M. (2016). Social media photography: construing subjectivity in Instagram
images. Visual Communication, 15(3), 271-292.
中文文獻
1. 何清雅、房美玉 (2005)。日薪人員工作壓力與工作滿意之研究,中央大學人力資源管理所碩士論文,未出版,桃園市。
2. 吳宇泓 (2015)。社群網站採用因素與自我揭露研究:從臉書到Instagram,
世新大學廣播電視電影學研究所碩士論文,未出版,台北市。
3. 林祐輿 (2009)。影響部落客自我揭露意圖因素之研究—以台灣地區為例,朝科科技大學資訊管理研究所碩士論文,台中市。
4. 邵健、章成志、李蕾 (2015)。Hashtag 研究綜述,現代圖書情報技術,263 (10),40-49。
5. 俞菁、邱海棠、曾馨瑩 (2012)。社群媒體中的自我揭露—以Facebook為例,中華傳播學會。
6. 郭志純(2003)。國民小學教師工作壓力、社會支持與職業怠倦之研究,國立嘉義大學國民教育研究所碩士論文,未出版,嘉義市。
7. 陳世志(2002)。矯正機構基層戒護管理人員的工作壓力、工作滿意與工作倦怠之相關研究,國立中山大學公共事務管理研究所碩士論文,高雄市。
8. 黃俊英 (1991)。多變量分析,第4版,台北:華泰。
9. 黃寶園(1998)。教師工作壓力與職業倦怠,諮商與輔導,154期,42。
10. 楊志堅、張家榮 (2000)。群集分析介紹,進修通訊年刊,6,42-49。
11. 蔡嬑佳 (2015)。視覺人生大佈局-探討Instagram
使用者如何運用相片呈現自我身份認同,國立中山大學行銷傳播管理研究所碩士論文,未出版,高雄市。
12. 鄭宇君、陳百齡 (2013)。探索2012 台灣總統大選之社交媒體浮現社群:鉅量資料分析取徑,中華傳播學會年會論文,台北市。
網路文獻
1. Dale, H. (2015). Hashtag activism: well meaning or self promotion dressed up as charity?, from http://www.theage.com.au/comment/hashtag-activism-well-meaning-or-self-
promotion-dressed-up-as-charity-20150113-12n29r.html, accessed on June 2017.
2. Kantar TNS (2016). Connected Life, from http://connectedlife.tnsglobal.com/, accessed on March 2017.
3. Piper Jaffray & Co. (2016). The Taking Stock With Teens, from
http://www.piperjaffray.com/3col.aspx?id=4035, accessed on March 2017.
4. Shively, K. (2012). 54% of Top Brands Now Active on Instagram [Study], from
https://simplymeasured.com/blog/54-percent-of-top-brands-now-active-on-
instagram/#sm.0001vwxuljcwtcp3v8f2n93fmnubv, accessed on March 2017.
5. yes123求職網 (2016)。2016年11月勞工請休假與職業倦怠調查,
取自2017年3月,
http://www.yes123.com.tw/admin/white_paper/index_detail.asp?id=20161108150912
6. 財團法人台灣網路資訊中心 (Taiwan Network Information Center, TWNIC) (2016)。2016年台灣寬頻網路使用調查報告,取自2017年3月,
www.twnic.net.tw/download/200307/20160922e.pdf
7. 財團法人台灣網路資訊中心 (Taiwan Network Information Center, TWNIC) (2016)。2016 年台灣無線網路使用調查,取自2017年3月
www.twnic.net.tw/download/200307/20170109e.pdf
8. 國家發展委員會 (2016)。105年持有手機民眾數位機會調查報告,
取自2017年3月,
http://www.ndc.gov.tw/cp.aspx?n=55c8164714dfd9e9
9. 張蕙娟、李庭萱 (2016)。HASHTAG之應用與NIKE主題行銷活動 #BETTERFORIT,Bpaper,42期,取自2017年5月,http://www.bpaper.org.tw/practice/39-04/
10. 創市際市場研究顧問公司 (2016)。社群網站
Instagram–使用行為調查,取自2017年3月,
http://www.ixresearch.com/news/news_02_05_16
11. 創市際市場研究顧問公司 (2016)。社群網站的使用行為,取自2017年5月,
https://rocket.cafe/talks/78006
12. 遠見雜誌 (2015)。國人生活壓力大調查,取自2017年3月,
https://www.gvm.com.tw/webonly_content_5664.html