| 研究生: |
蔡旻珈 Tsai, Min-Chia |
|---|---|
| 論文名稱: |
整合傳播理論與計畫行為理論探討網路模因特性對社群媒體使用者分享意圖的影響 Integrating Communication Theory and Theory of Planned Behavior Explore the Influence of the Internet Memes’ Characteristics on the Social Media Users’ Sharing Intention |
| 指導教授: |
王維聰
Wang, Wei-Tsong |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 資訊管理研究所 Institute of Information Management |
| 論文出版年: | 2022 |
| 畢業學年度: | 110 |
| 語文別: | 中文 |
| 論文頁數: | 78 |
| 中文關鍵詞: | 網路模因 、計畫行為理論 、傳播理論 、吸引力 、分享意圖 |
| 外文關鍵詞: | Internet memes, Theory of planned behavior, Communication theory, Attractiveness, Sharing intention |
| 相關次數: | 點閱:147 下載:0 |
| 分享至: |
| 查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
隨著科技的日新月異以及網路的蓬勃發展,人們互動與交換資訊的方式不再侷限於實體管道,而是有越來越多的網路媒體可以選擇。近年來網路模因在社群媒體間掀起潮流,成為了隨處可見以及隨手可得的傳播內容,網路模因增加了社群媒體使用者之間的互動、促進了使用者的顧客參與以及社會參與,進而提升了熱門話題的傳播速度,並且如病毒般的快速在社群媒體間擴散,因此,網路模因的特性如何吸引社群媒體使用者,並改變使用者的行為態度與行為意圖,促使其能夠以高速傳播的速度,達到快速擴散的效果,便成為了值得我們探討的議題,故本研究整合了傳播理論 (Communication Theory) 與計畫行為理論 (Theory of Planned Behavior, TPB) ,藉以探討網路模因的特性對社群媒體使用者的分享意圖所產生的影響,使大眾能夠更精準的了解使用者的喜好,以利決策與政策的實施。
本研究針對曾經於Facebook與網路模因相關粉絲專頁互動之社群媒體使用者進行問卷的發放與調查,共回收有效問卷323份,再透過結構方程模式進行驗證性分析,研究結果顯示網路模因的特性會對社群媒體使用者的態度與意圖產生正向影響,而幽默性、情緒強度與傳播性皆會對不同面向的使用者態度產生影響,進而影響其分享意圖。因此,如何透過網路模因精準地抓住社群媒體使用者的喜好,達到提高資訊傳播的速度並如病毒般的傳播效果,以提升處事效率與效益便成為了現今的一大課題。
The rapid development of science and technology has changed human life in the modern world. More and more people use social media to interact with other people and share information. However, some social media users enjoy watching some posts about Internet memes; therefore, Internet memes set off a trend in social media. They thus promote customer engagement and social engagement of users, thus increasing the speed at which the topic spreads.
This study integrates communication theory and theory of planned behavior (TPB) to explore the impact of the Internet memes' characteristics on the social media users' sharing intention. By applying structural equation modeling techniques to investigate the model proposed in this study, the hypotheses are empirically validated based on internet survey data of 323 Facebook users who have interacted with Internet memes-related fan pages. The findings suggest that the characteristics of Internet memes' humor, emotional intensity, and spreadability all impact different types of user attitudes, which in turn affect their share intention. Therefore, if we could accurately grasp the preferences of social media users through online expressions, the efficiency of policy implementation could be improved.
Aguilar, G. K., Campbell, H. A., Stanley, M., & Taylor, E. (2017). Communicating mixed messages about religion through internet memes. Information, Communication & Society, 20(10), 1498-1520. doi:10.1080/1369118X.2016.1229004
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Kuhl, J. & Beckman, J. (Eds.), Action control: From cognition to behavior (pp. 11-39). Berlin, Heidelberg: Springer.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. doi:10.1016/0749-5978(91)90020-T
Ajzen, I. (2020). The theory of planned behavior: Frequently asked questions. Human Behavior and Emerging Technologies, 2(4), 314-324. doi:10.1002/hbe2.195
Al-Dhaen, F., Hou, J., Rana, N. P., & Weerakkody, V. (2021). Advancing the understanding of the role of responsible AI in the continued use of IoMT in healthcare. Information Systems Frontiers, ahead-of-print(ahead-of-print). doi:10.1007/s10796-021-10193-x
Al-Maatouk, Q., Othman, M. S., Alsayed, A. O., Al-Rahmi, A. M., Abuhassna, H., & Al-Rahmi, W. M. (2020). Applying communication theory to structure and evaluate the social media platforms in academia. International Journal of Advanced Trends in Computer Science and Engineering, 9(2), 1505-1517.
doi: 10.30534/ijatcse/2020/92922020
Alalwan, A. A. (2018). Investigating the impact of social media advertising features on customer purchase intention. International Journal of Information Management, 42, 65-77. doi:10.1016/j.ijinfomgt.2018.06.001
Alalwan, N., Al-Rahmi, W. M., Alfarraj, O., Alzahrani, A., Yahaya, N., & Al-Rahmi, A. M. (2019). Integrated three theories to develop a model of factors affecting students’ academic performance in higher education. IEEE Access, 7, 98725-98742. doi: 10.1109/ACCESS.2019.2928142
Amador, P. V., & Amador, J. M. (2017). Academic help seeking: A framework for conceptualizing Facebook use for higher education support. TechTrends, 61(2), 195-202. doi:10.1007/s11528-016-0135-3
Bagozzi, R. P., Gopinath, M., & Nyer, P. U. (1999). The role of emotions in marketing. Journal of the Academy of Marketing Science, 27(2), 184-206.
doi:10.1177/0092070399272005
Bagozzi, R. P., & Pieters, R. (1998). Goal-directed emotions. Cognition and Emotion, 12(1), 1-26. doi:10.1080/026999398379754
Barry, J. M., & Graça, S. S. (2018). Humor effectiveness in social video engagement. Journal of Marketing Theory and Practice, 26(1-2), 158-180.
doi:10.1080/10696679.2017.1389247
Baxendale, S. (2021). Epilepsy: Lessons for clinicians from popular memes on social media. Epilepsy & Behavior, 118, 107899. doi:10.1016/j.yebeh.2021.107899
Bazi, S., Filieri, R., & Gorton, M. (2020). Customers’ motivation to engage with luxury brands on social media. Journal of Business Research, 112, 223-235. doi: 10.1016/j.jbusres.2020.02.032
Bebić, D., & Volarevic, M. (2018). Do not mess with a meme: The use of viral content in communicating politics. Communication & Society, 31(3), 43-56.
doi:10.15581/003.31.3.43-56
Benetoli, A., Chen, T. F., & Aslani, P. (2019). Consumer perceptions of using social media for health purposes: Benefits and drawbacks. Health Informatics Journal, 25(4), 1661-1674. doi:10.1177/1460458218796664
Berger, J., & Milkman, K. L. (2012). What makes online content viral? Journal of Marketing Research, 49(2), 192-205. doi:10.1509/jmr.10.0353
Berki-Kiss, D., & Menrad, K. (2022). The role emotions play in consumer intentions to make pro-social purchases in Germany – An augmented theory of planned behavior model. Sustainable Production and Consumption, 29, 79-89.
doi:10.1016/j.spc.2021.09.026
Bock, G. W., Zmud, R. W., Kim, Y. G., & Lee, J. N. (2005). Behavioral intention formation in knowledge sharing: Examining the roles of extrinsic motivators, social-psychological forces, an organizational climate. MIS Quarterly, 29(1), 87–111. doi:10.2307/25148669
Bollen, K. A. (1989) Structural equations with latent variables. New York, NY: Wiley.
Borges-Tiago, M. T., Tiago, F., & Cosme, C. (2019). Exploring users' motivations to participate in viral communication on social media. Journal of Business Research, 101, 574-582. doi:10.1016/j.jbusres.2018.11.011
Breckler, S. J. (1984). Empirical validation of affect, behavior, and cognition as distinct components of attitude. Journal of Personality and Social Psychology, 47(6), 1191. doi:10.1037/0022-3514.47.6.1191
Brody, N. (2018). Opting out of social media: Online communication attitudes mediate the relationship between personality factors and Facebook non-use. Southern Communication Journal, 83(2), 75-88. doi:10.1080/1041794X.2017.1413415
Brubaker, P. J., Church, S. H., Hansen, J., Pelham, S., & Ostler, A. (2018). One does not simply meme about organizations: Exploring the content creation strategies of user-generated memes on Imgur. Public Relations Review, 44(5), 741-751. doi: 10.1016/j.pubrev.2018.06.004
Chang, H. H., Wong, K. H., & Li, S. Y. (2017). Applying push-pull-mooring to investigate channel switching behaviors: M-shopping self-efficacy and switching costs as moderators. Electronic Commerce Research and Applications, 24, 50-67. doi: 10.1016/j.elerap.2017.06.002
Chen, C.-H., Huang, C.-Y., & Chou, Y.-Y. (2019a). Effects of augmented reality-based multidimensional concept maps on students’ learning achievement, motivation and acceptance. Universal Access in the Information Society, 18(2), 257-268. doi: 10.1007/s10209-017-0595-z
Chen, T.-Y., Yeh, T.-L., & Chang, C.-I. (2020). How different advertising formats and calls to action on videos affect advertising recognition and consequent behaviours. The Service Industries Journal, 40(5-6), 358-379. doi:10.1080/02642069.2018.1480724
Chen, X., Tao, D., & Zhou, Z. (2019b). Factors affecting reposting behaviour using a mobile phone-based user-generated-content online community application among Chinese young adults. Behaviour & Information Technology, 38(2), 120-131. doi:10.1080/0144929X.2018.1515985
Chen, Y., Liang, C., & Cai, D. (2018). Understanding WeChat users’ behavior of sharing social crisis information. International Journal of Human–Computer Interaction, 34(4), 356-366. doi:10.1080/10447318.2018.1427826
Cheunkamon, E., Jomnonkwao, S., & Ratanavaraha, V. (2020). Determinant factors influencing Thai tourists’ intentions to use social media for travel planning. Sustainability, 12(18), 7252. doi:10.3390/su12187252
Cooper, C. D. (2005). Just joking around? Employee humor expression as an ingratiatory behavior. Academy of Management Review, 30(4), 765-776.
doi:10.5465/amr.2005.18378877
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. doi:10.2307/249008
Dawkins, R. (1976). The selfish gene. New York, NY: Oxford U. Press.
Diefenbach, M. A., Weinstein, N. D., & O'Reilly, J. (1993). Scales for assessing perceptions of health hazard susceptibility. Health Education Research, 8(2), 181-192. doi:10.1093/her/8.2.181
Dolan, R., Conduit, J., Frethey-Bentham, C., Fahy, J., & Goodman, S. (2019). Social media engagement behavior. European Journal of Marketing, 53(10), 2213-2243. doi:10.1108/EJM-03-2017-0182
Dong, Y., Dong, L. (2021). Influence Mechanism of Mobile Social Network Users’ Product Recommendation Information on Consumers’ Intention to Participate Sharing Economy. In Abawajy, J., Xu, Z., Atiquzzaman, M., Zhang, X. (Eds.), 2021 International Conference on Applications and Techniques in Cyber Intelligence. ATCI 2021. Advances in Intelligent Systems and Computing, 1398. Cham, Switzerland: Springer. doi:10.1007/978-3-030-79200-8_15
Duffy, A., Tandoc, E., & Ling, R. (2020). Too good to be true, too good not to share: The social utility of fake news. Information, Communication & Society, 23(13), 1965-1979. doi:10.1080/1369118X.2019.1623904
Dynel, M. (2016). “I has seen image macros!” advice animals memes as visual-verbal jokes. International Journal of Communication, 10, 660-668.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
Fishbein, M., & Ajzen, I. (2010). Predicting and changing behavior: The reasoned action approach. New York, NY: Psychology Press.
Ge, J., & Gretzel, U. (2018). Impact of humour on firm-initiated social media conversations. Information Technology & Tourism, 18, 61-83. doi:10.1007/s40558-017-0097-0
Gioia, F., & Boursier, V. (2021a). Young adults’ attitudes toward online self-disclosure and social connection as predictors of a preference for online social interactions: The mediating effect of relational closeness. Atlantic Journal of Communication, ahead-of-print(ahead-of-print). doi:10.1080/15456870.2021.1952205
Gioia, F., Fioravanti, G., Casale, S., & Boursier, V. (2021b). The effects of the fear of missing out on people’s social networking sites use during the COVID-19 pandemic: The mediating role of online relational closeness and individuals' online communication attitude. Frontiers in Psychiatry, 12, 620442.
doi: 10.3389/fpsyt.2021.620442
Goyer, R. S. (1970). Communication, communicative process meaning: Toward a unified theory. Journal of Communication, 20(1), 4-16. doi:10.1111/j.1460-2466.1970.tb00860.x
Gu, J., Wang, X., & Lu, T. (2020). I like my app but I wanna try yours: Exploring user switching from a learning perspective. Internet Research, 30(2), 611-630. doi:10.1108/INTR-07-2018-0310
Gvili, Y., & Levy, S. (2021). Consumer engagement in sharing brand-related information on social commerce: The roles of culture and experience. Journal of Marketing Communications, 27(1), 53-68. doi:10.1080/13527266.2019.1633552
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM). 2nd Edition. Thousand Oaks: Sage.
Hair, J.F., Risher, J.J., Sarstedt, M. & Ringle, C.M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24. doi: 10.1108/EBR-11-2018-0203
Hansen, T., Jensen, J. M., & Solgaard, H. S. (2004). Predicting online grocery buying intention: A comparison of the theory of reasoned action and the theory of planned behavior. International Journal of Information Management, 24(6), 539-550. doi: 10.1016/j.ijinfomgt.2004.08.004
Harber, K. D., & Cohen, D. J. (2005). The emotional broadcaster theory of social sharing. Journal of Language and Social Psychology, 24(4), 382-400.
doi: 10.1177/0261927X05281426
Harshavardhan, V., Wilson, D., & Kumar, M. V. (2019). Humour discourse in internet memes: An aid in ESL classrooms. Asia Pacific Media Educator, 29(1), 41-53. doi: 10.1177/1326365X19842023
Heinberg, M., Ozkaya, H.E. & Taube, M. (2017). The influence of global and local iconic brand positioning on advertising persuasion in an emerging market setting. Journal of International Business Studies, 48, 1009-1022. doi:10.1057/s41267-017-0071-2
Hendijani Fard, M., & Marvi, R. (2020). Viral marketing and purchase intentions of mobile applications users. International Journal of Emerging Markets, 15(2), 287-301. doi:10.1108/IJOEM-06-2018-0291
Hinzo, A. M., & Clark, L. S. (2019). Digital survivance and Trickster humor: Exploring visual and digital Indigenous epistemologies in the #NoDAPL movement. Information, Communication & Society, 22(6), 791-807.
doi: 10.1080/1369118X.2019.1573911
Ho, C.-T. B., & Gebsombut, N. (2019). Communication factors affecting tourist adoption of social network sites. Sustainability, 11(15), 4198. doi:10.3390/su11154198
Hong, Y., Wan, M., & Li, Z. (2021). Understanding the health information sharing behavior of social media users: An empirical study on WeChat. Journal of Organizational and End User Computing, 33(5), 180-203.
doi: 10.4018/JOEUC.20210901.oa9
Hou, F., Guan, Z., Li, B., & Chong, A. Y. L. (2020). Factors influencing people’s continuous watching intention and consumption intention in live streaming. Internet Research, 30(1), 141-163. doi:10.1108/INTR-04-2018-0177
Huang, G. I., Chen, Y. V., & Wong, I. A. (2020). Hotel guests’ social commerce intention. International Journal of Contemporary Hospitality Management, 32(2), 706-729. doi:10.1108/IJCHM-04-2019-0380
Johnson, J. (Ed.). (2021, September 10). Global Digital Population as of January 2021. Retrieved November 19, 2021, from https://www.statista.com/statistics/617136/digital-population-worldwide/
Kalogiannidis, S. (2020). Impact of effective business communication on employee performance. European Journal of Business and Management Research, 5(6). doi: 10.24018/ejbmr.2020.5.6.631
Karandashev, V., Evans, N. D., Zarubko, E., Neto, F., Evans, M., Artemeva, V., Morgan, K.A.D., Feybesse, C., Surmanidze, L. (2020). Physical attraction sacale—short version: Cross-cultural validation. Journal of Relationships Research, 11. doi:10.1017/jrr.2020.17
Kim, J.-h., Kim, G.-j., Choi, H.-j., Seok, B.-i., & Lee, N.-h. (2019). Effects of social network services (SNS) subjective norms on SNS addiction. Journal of Psychology in Africa, 29(6), 582-588. doi:10.1080/14330237.2019.1694735
Kim, S. E., Kim, H. L., & Lee, S. (2021). How event information is trusted and shared on social media: a uses and gratification perspective. Journal of Travel & Tourism Marketing, 38(5), 444-460. doi:10.1080/10548408.2021.1943600
Kim, S. S. (2020). Purchase intention in the online open market: Do concerns for e-commerce really matter? Sustainability, 12(3), 773. doi: 10.3390/su12030773
Kim, Y. J., Njite, D., & Hancer, M. (2013). Anticipated emotion in consumers’ intentions to select eco-friendly restaurants: Augmenting the theory of planned behavior. International Journal of Hospitality Management, 34, 255-262. doi: 10.1016/j.ijhm.2013.04.004
Kline, R. B. (2015). Principles and practice of structural equation modeling. 4th Edition. New York: Guilford Press.
Klobas, J. E., McGill, T. J., Moghavvemi, S., & Paramanathan, T. (2018). Compulsive YouTube usage: A comparison of use motivation and personality effects. Computers in Human Behavior, 87, 129-139. doi: 10.1016/j.chb.2018.05.038
Kourtit, K., Nijkamp, P., & Romão, J. (2019). Cultural heritage appraisal by visitors to global cities: The use of social media and urban analytics in urban buzz research. Sustainability, 11(12), 3470. doi: 10.3390/su11123470
Ledbetter, A. M. (2009). Measuring online communication attitude: Instrument development and validation. Communication Monographs, 76(4), 463-486. doi: 10.1080/03637750903300262
Ledbetter, A. M., & Mazer, J. P. (2014). Do online communication attitudes mitigate the association between Facebook use and relational interdependence? An extension of media multiplexity theory. New Media & Society, 16(5), 806-822. doi: 10.1177/1461444813495159
Lee, H.-H., Liang, C.-H., Liao, S.-Y., & Chen, H.-S. (2019). Analyzing the intention of consumer purchasing behaviors in relation to internet memes using VAB model. Sustainability, 11(20), 5549. doi:10.3390/su11205549
Leung, X. Y., & Jiang, L. (2018). How do destination Facebook pages work? An extended TPB model of fans’ visit intention. Journal of Hospitality and Tourism Technology, 9(3), 397-416. doi:10.1108/JHTT-09-2017-0088
Li, C.-Y. (2017). Why do online consumers experience information overload? An extension of communication theory. Journal of Information Science, 43(6), 835-851. doi: 10.1177/0165551516670096
Liew, T. W., Zin, N. A. M., & Sahari, N. (2017). Exploring the affective, motivational and cognitive effects of pedagogical agent enthusiasm in a multimedia learning environment. Human-centric Computing and Information Sciences, 7, 9. doi: 10.1186/s13673-017-0089-2
Lin, H. C., Lee, N. C., & Lu, Y.-C. (2021). The mitigators of ad irritation and avoidance of YouTube skippable in-stream ads: An Empirical Study in Taiwan. Information, 12(9), 373. doi:10.3390/info12090373
Lin, Y.-L. & Wang, W.-T. (2021). The influence of supervisor proactivity on perceived job demands and job outcomes among information technology subordinates in IT-related service projects. Information Technology & People, ahead-of-print(ahead-of-print). doi:10.1108/ITP-04-2021-0250
Masek, A., Hashim, S., & Ismail, A. (2019). Integration of the humour approach with student’s engagement in teaching and learning sessions. Journal of Education for Teaching, 45(2), 228-233. doi:10.1080/02607476.2018.1548169
Nabi, R. L., Moyer-Gusé, E., & Byrne, S. (2007). All joking aside: A serious investigation into the persuasive effect of funny social issue messages. Communication Monographs, 74(1), 29-54. doi:10.1080/03637750701196896
Paul, J., Modi, A., & Patel, J. (2016). Predicting green product consumption using theory of planned behavior and reasoned action. Journal of Retailing and Consumer Services, 29, 123-134. doi:10.1016/j.jretconser.2015.11.006
Podsakoff, P.M., MacKenzie, S.B., Lee, J.Y. and Podsakoff, N.P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879-903. doi:10.1037/0021-9010.88.5.879
Raza, S. A., Qazi, W., Shah, N., Qureshi, M. A., Qaiser, S., & Ali, R. (2020). Drivers of intensive Facebook usage among university students: An implications of U&G and TPB theories. Technology in Society, 62, 101331.
doi:10.1016/j.techsoc.2020.101331
She, J., & Zhang, T. (2019). The impact of headline features on the attraction of online financial articles. International Journal of Web Information Systems, 15(5), 510-534. doi:10.1108/IJWIS-11-2018-0084
Shifman, L. (2013). Memes in a digital world: Reconciling with a conceptual troublemaker. Journal of Computer-Mediated Communication, 18(3), 362-377. doi:10.1111/jcc4.12013
Shifman, L. (2014). Memes in digital culture. Cambridge, MA: MIT press.
Singh, J., & Crisafulli, B. (2020). How intensity of cause-related marketing guilt appeals influences consumers: The roles of company motive and consumer identification with the brand. Journal of Advertising Research, 60(2), 148-162. doi:10.2501/JAR-2018-049
Statista Research Department (Ed.). (2021, November 16). Most Popular Social Networks Worldwide as of October 2021, Ranked by Number of Active Users. Retrieved November 19, 2021, from https://www.statista.com/statistics/272014/global-social-networks-ranked-by-number-of-users/
Sun, S., Rubin, A. M., & Haridakis, P. M. (2008). The role of motivation and media involvement in explaining internet dependency. Journal of Broadcasting & Electronic Media, 52(3), 408-431. doi:10.1080/08838150802205595
Tang, Z., & Chen, L. (2020). An empirical study of brand microblog users’ unfollowing motivations: The perspective of push-pull-mooring model. International Journal of Information Management, 52, 102066. doi:10.1016/j.ijinfomgt.2020.102066
Teng, H., Lo, C.-F., & Lee, H.-H. (2021). How do internet memes affect brand image? Online Information Review, 46(2), 304-318 doi:10.1108/OIR-05-2020-0192
Teng, S., Wei Khong, K., Wei Goh, W., & Yee Loong Chong, A. (2014). Examining the antecedents of persuasive eWOM messages in social media. Online Information Review, 38(6), 746-768. doi:10.1108/OIR-04-2014-0089
Van Dijck, J. (2013). The culture of connectivity: A critical history of social media. New York, NY: Oxford University Press.
Van Ruler, B. (2018). Communication theory: An underrated pillar on which strategic communication rests. International Journal of Strategic Communication, 12(4), 367-381. doi:10.1080/1553118X.2018.1452240
Wang, X., Lin, X., & Spencer, M. K. (2019a). Exploring the effects of extrinsic motivation on consumer behaviors in social commerce: Revealing consumers’ perceptions of social commerce benefits. International Journal of Information Management, 45, 163-175. doi:10.1016/j.ijinfomgt.2018.11.010
Wang, Y. S., Tseng, T. H., Wang, W. T., Shih, Y. W., & Chan, P. Y. (2019b). Developing and validating a mobile catering app success model. International Journal of Hospitality Management, 77, 19-30. doi: 10.1016/j.ijhm.2018.06.002
Warren, C., Barsky, A., & McGraw, A. P. (2018). Humor, comedy, and consumer behavior. Journal of Consumer Research, 45(3), 529-552. doi:10.1093/jcr/ucy015
Whiting, A., & Williams, D. (2013). Why people use social media: A uses and gratifications approach. Qualitative Market Research, 16(4), 362-369. doi:10.1108/QMR-06-2013-0041
Wiggins, B. E., & Bowers, G. B. (2015). Memes as genre: A structurational analysis of the memescape. New Media & Society, 17(11), 1886-1906.
doi: 10.1177/1461444814535194
Wood, M. A. (2020). Policing’s “meme strategy”: Understanding the rise of police social media engagement work. Current Issues in Criminal Justice, 32(1), 40-58. doi:10.1080/10345329.2019.1658695
Xu, Y., Ye, Y., & Liu, Y. (2022). Understanding Virtual Gifting in Live Streaming by the Theory of Planned Behavior. Human Behavior and Emerging Technologies, ahead-of-print(ahead-of-print), 8148077. doi:10.1155/2022/8148077
Yang, H.-L., & Chao, A. F. Y. (2018). Sentiment annotations for reviews: An information quality perspective. Online Information Review, 42(5), 579-594. doi:10.1108/OIR-04-2017-0114
Yoon, D. (2020). The job satisfaction level analysis for the research environment and the research production. Cogent Business & Management, 7(1), 1818364. doi: 10.1080/23311975.2020.1818364
Zheng, X., Men, J., Xiang, L., & Yang, F. (2020). Role of technology attraction and parasocial interaction in social shopping websites. International Journal of Information Management, 51, 102043. doi:10.1016/j.ijinfomgt.2019.102043
Zulli, D., & Zulli, D. J. (2020). Extending the Internet meme: Conceptualizing technological mimesis and imitation publics on the TikTok platform. New Media & Society, ahead-of-print(ahead-of-print). doi:10.1177/1461444820983603
校內:2027-07-05公開