Sosyal Paylaşım Sitelerinde Bilgi Paylaşma Niyeti ve Cinsiyetin Rolü

Öz

Sosyal paylaşım siteleri; kullanıcıların içerik paylaşabildikleri ve diğer kullanıcılarla iletişim ve etkileşim kurabildikleri alanlardır. Türkiye’de en çok kullanılan sosyal paylaşım siteleri sırasıyla Youtube, Instagram, Whatsapp, Facebook ve Twitter’dir. Bireyler sosyal paylaşım sitelerinde geçirdikleri süre boyunca durum güncellemesi, fotoğraf, video, yorum, deneyim veya reklam paylaşımı vb. gibi farklı türlerde bilgi paylaşımında bulunmaktadırlar. Bu bilgi akışı sonucunda sosyal paylaşım siteleri kullanıcıları hakkında pek çok veri elde etmekte ve söz konusu verilerle ticari kar sağlayabilmektedir. Bu çalışmanın amacı kullanıcıları sosyal paylaşım sitelerinde bilgi paylaşma niyetine yönelten unsurların ortaya çıkarılması ve bu davranışının kadın ve erkekler üzerinde nasıl farklılaştığını belirlemektir. Bu amaca yönelik olarak bu çalışmada doğrulayıcı faktör analizi (DFA), yapısal eşitlik modeli (YEM) analizi, ölçüm denklik testi ve çoklu grup analizi (ÇGA) gerçekleştirilmiştir. Analizler sonucunda; mahremiyet riskinin bilgi paylaşma tutumunu negatif ve bağlılığın pozitif etkilediği ve bilgi paylaşma tutumu ve öznel normların bilgi paylaşma niyetini pozitif etkilediği bulunmuştur. Sosyal bağların bilgi paylaşma tutumu üzerindeki etkisi ise anlamlı bulunmamıştır. Son olarak, yalnızca tutumun sosyal paylaşım sitelerinde bilgi paylaşma niyeti üzerindeki etkisinin cinsiyete göre farklılaştığı ve bu etkinin kadınlarda erkeklerden daha fazla olduğu bulunmuştur.

Anahtar Kelimeler

• Sosyal Paylaşım Siteleri
• Bilgi Paylaşma
• DFA
• YEM
• Çoklu Grup Analizi

Intention to Share Information on Social Sharing Sites and the Role of Gender

Öz

Social networking sites; are areas where users can share content and communicate and interact with other users. The most used social networking sites in Turkey are Youtube, Instagram, Whatsapp, Facebook and Twitter, respectively. Individuals can share status updates, photos, videos, comments, experiences or advertisements during their time on social networking sites. They share different types of information, as a result of this flow of information, social networking sites obtain a lot of data about their users and can generate commercial profit with the data. The aim of this study is to reveal the factors that lead users to share information on social networking sites and to determine how this behavior differs on men and women. For this purpose, confirmatory factor analysis (CFA), structural equation model (SEM) analysis, measurement equivalence test and multiple group analysis (MGA) were performed in this study. As a result of the analysis; It was found that the risk of privacy affects the information sharing attitude negatively and the commitment effects the information sharing attitude positively and the information sharing attitude and subjective norms both affect the information sharing intention positively. The effect of social ties on knowledge sharing attitude was not found significant. Finally, it was found that only the effect of attitude on the intention to share information on social networking sites differs according to gender, and this effect is higher in women than in men.

Anahtar Kelimeler

• Social Network Sites
• Information Sharing
• CFA
• SEM
• Multi Group Analysis

Kaynakça

1. Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.
2. Arpaci, I., Baloğlu, M., & Kesici, Ş. (2019). A multi-group analysis of the effects of individual differences in mindfulness on nomophobia. Information Development, 35(2), 333–341.
3. Arpaci, I. (2019). Culture and nomophobia: The role of vertical versus horizontal collectivism in predicting nomophobia. Information Development, 35(1), 96–106.
4. Arpaci, Ibrahim. (2020). The Influence of Social Interactions and Subjective Norms on Social Media Postings. Journal of Information and Knowledge Management, 19(3), 1–10. https://doi.org/10.1142/S0219649220500239
5. Baker, R. K., & White, K. M. (2010). Predicting adolescents’ use of social networking sites from an extended theory of planned behaviour perspective. Computers in Human Behavior, 26(6), 1591–1597. https://doi.org/10.1016/j.chb.2010.06.006
6. Bilgihan, A., & Kandampully, J. (2014). Generation Y’s dining information seeking and sharing behavior on social networking sites An exploratory study. International Journal of Contemporary Hospitality Management, 26(3), 349–366. https://doi.org/10.1108/IJCHM-11-2012-0220
7. Bolton, R. N., Parasuraman, A., Hoefnagels, A., Migchels, N., Kabadayi:, Gruber, T., Loureiro, Y. K., Solnet, D. (2013). Understanding Generation Y and their use of social media: A review and research agenda. Journal of Service Management, 24(3), 245–267. https://doi.org/10.1108/09564231311326987
8. Brislin, R. W., Lonner, W. J., & Thorndike, R. M. (1973). Cross-cultural research methods (Vol. 11). New York: J. Wiley.

9. Çetin, F., & Basım, H. N. (2012). Örgütsel Psikolojik Sermaye: Bir Ölçek Uyarlama Çalışması. Amme İdaresi Dergisi, 45(1), 121–137.
10. Chai, S., Das, S., & Rao, H. (2011). Factors affecting bloggers’ knowledge sharing: An investigation across gender. Journal of Management Information Systems, 28(3), 309–342. https://doi.org/10.2753/MIS0742-1222280309
11. Chai, S., & Kim, M. (2012). A socio-technical approach to knowledge contribution behavior: An empirical investigation of social networking sites users. International Journal of Information Management, 32(2), 118–126. https://doi.org/10.1016/j.ijinfomgt.2011.07.004
12. Cheikh-Ammar, M., & Barki, H. (2016). The Influence of Social Presence , Social Exchange and Feedback Features on SNS Continuous Use : The Facebook Context. Journal of Organizational and End User Computing, 28(2), 33–52. https://doi.org/10.4018/JOEUC.2016040103
13. Cheung, G. W., & Rensvold, R. B. (2002). Structural Equation Modeling Evaluating Goodness-of-Fit Indexes for Testing Measurement Invariance. Structural Equation Modeling, 9(2), 233–255. https://doi.org/10.1207/S15328007SEM0902_5
14. Choi, J. H. (2015). Putting The Social Into Social Network Sites: A Knowledge Sharing Perspective (Doctoral Thesis). University of Colorado, Colorado.
15. Craig Van Slyke, Shim, J. T., Johnson, R., & Jiang, J. (2006). Concern for Information Privacy and Online Consumer Purchasing. Journal of the Association for Information Systems, 7(6), 415–444. https://doi.org/10.17705/1jais.00092
16. Dwyer, P. D., Gilkeson, J. H., & List, J. A. (2002). Gender differences in revealed risk taking: Evidence from mutual fund investors. Economics Letters, 76(2), 151–158. https://doi.org/10.1016/S0165-1765(02)00045-9
17. Eagly, A. H., & Carli, L. L. (1981). Sex of researchers and sex-typed communications as determinants of sex differences in influenceability: A meta-analysis of social influence studies. Psychological Bulletin, 90(1), 1.
18. Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The Benefits of Facebook “Friends:” Social Capital and College Students’ Use of Online Social Network Sites. Journal of Computer-Mediated Communication, 12(4), 1143–1168. https://doi.org/10.1111/j.1083-6101.2007.00367.x
19. Fishbein, M. (1963). An investigation of the relationships between beliefs about an object and the attitude toward that object. Human Relations, 16(3), 233–239.
20. Fishbein, Martin & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An introduction to theory and research. Philosophy and Rhetoric, 10(2), 177-188.
21. Gürbüz, S. (2019). AMOS ile yapısal eşitlik modellemesi. Ankara: Seçkin Yayıncılık.
22. Gustafson, P. E. (1998). Gender differences in risk perception: Theoretical and methodological perspectives. Risk Analysis, 18(6), 805–811. https://doi.org/10.1023/B:RIAN.0000005926.03250.c0
23. Gvili, Y., Levy, S., & 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. https://doi.org/10.1080/13527266.2019.1633552
24. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2009). Multivariate Data Analysis (Seventh). NewYork: Prentice Hall.
25. Hajli, N., & Lin, X. (2016). Exploring the Security of Information Sharing on Social Networking Sites : The Role of Perceived Control of Information. Journal of Business Ethics, 133, 111–123. https://doi.org/10.1007/s10551-014-2346-x
26. Hansen, J. M., Saridakis, G., & Benson, V. (2018). Computers in Human Behavior Risk , trust , and the interaction of perceived ease of use and behavioral control in predicting consumers ’ use of social media for transactions. Computers in Human Behavior, 80, 197–206. https://doi.org/10.1016/j.chb.2017.11.010
27. Hargittai, E., & Hsieh, Y. P. (2010). Predictors and consequences of differentiated practices on social network sites. Communication & Society, 13(4), 515–536. https://doi.org/10.1080/13691181003639866
28. Ho, S. C., Ting, P. H., Bau, D. Y., & Wei, C. C. (2011). Knowledge-sharing intention in a virtual community: A study of participants in the Chinese wikipedia. Cyberpsychology, Behavior, and Social Networking, 14(9), 541–545. https://doi.org/10.1089/cyber.2010.0106
29. 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), 1–24. https://doi.org/10.4018/JOEUC.20210901.oa9
30. Ifinedo, P. (2017). Examining students’ intention to continue using blogs for learning: Perspectives from technology acceptance, motivational, and social-cognitive frameworks. Computers in Human Behavior, 72, 189–199. https://doi.org/10.1016/j.chb.2016.12.049
31. Jin, X. (2016). Information Sharing in the Era of Social Media Information Sharing (Master Thesis). University of Jyväskylä, Finland.
32. Kang, M. (2014). Understanding Public Engagement: Conceptualizing and Measuring its Influence on Supportive Behavioral Intentions. Journal of Public Relations Research, 26(5), 399–416. https://doi.org/10.1080/1062726X.2014.956107
33. Karnowski, V., Leonhard, L., & Sophie Kümpel, A. (2017). Why Users Share the News: A Theory of Reasoned Action-Based Study on the Antecedents of News- Sharing Behavior. Communication Research Reports, 35(3), 91–100. https://doi.org/10.1080/08824096.2017.1379984
34. Kayes, I., & Iamnitchi, A. (2017). Privacy and security in online social networks : A survey. Online Social Networks and Media, 3–4, 1–21. https://doi.org/10.1016/j.osnem.2017.09.001
35. Kılıç, A. F., ve Koyuncu, İ. (2017). Ölçek uyarlama çalışmalarının yapı geçerliği açısından incelenmesi. Pegem Atıf İndeksi, 415-438.
36. Kim, H. S., Cho, K. M., & Kim, M. (2021). Information-Sharing Behaviors Among Sports Fans Using #Hashtags. Communication & Sport, 9(4), 646–669. https://doi.org/10.1177/2167479519878466
37. Kim, J., Lee, C., & Elias, T. (2015). Factors affecting information sharing in social networking sites amongst university students. Online Information Review, 39(3), 290–309. https://doi.org/10.1108/OIR-01-2015-0022
38. Kline, R. B. (2016). Principle and practice of structural equation modelling (4. Baskı). New York, NY: The Guilford Press.
39. Ku, Y. C., Chen, R., & Zhang, H. (2013). Why do users continue using social networking sites? An exploratory study of members in the United States and Taiwan. Information and Management, 50(7), 571–581. https://doi.org/10.1016/j.im.2013.07.011
40. Lee, Jae-rock. (2020). Understanding factors affecting users’ social media continuance. Journal of the Korea Convergence Society, 11(7), 145–150.
41. Lee, Junghyo, Kim, J., & Young, J. (2020). The adoption of virtual reality devices: The technology acceptance model integrating enjoyment, social interaction, and strength of the social ties. Telematics and Informatics, 39(June 2018), 37–48. https://doi.org/10.1016/j.tele.2018.12.006
42. Li, K., Cheng, L., & Teng, C. (2020). Voluntary sharing and mandatory provision : Private information disclosure on social networking sites. Information Processing and Management, 57(1), 1–14. https://doi.org/10.1016/j.ipm.2019.102128
43. Liang, T.-P., Ho, Y.-T., Li, Y.-W., & Turban, E. (2011). What drives social commerce: The role of social support and relationship quality. International Journal of Electronic Commerce, 16(2), 69–90.
44. Lin, C. A., & Kim, T. (2016). Predicting user response to sponsored advertising on social media via the technology acceptance model. Computers in Human Behavior, 64, 710–718. https://doi.org/10.1016/j.chb.2016.07.027
45. Lin, H. C., Chen, Y. J., Chen, C. C., & Ho, W. H. (2018). Expectations of social networking site users who share and acquire health-related information. Computers and Electrical Engineering, 69, 808–814. https://doi.org/10.1016/j.compeleceng.2018.02.014
46. Lin, H. F. (2008). Determinants of successful virtual communities: Contributions from system characteristics and social factors. Information and Management, 45(8), 522–527. https://doi.org/10.1016/j.im.2008.08.002
47. Lin, X., Featherman, M., & Sarker, S. (2013). Information Sharing in the Context of Social Media: An Application of the Theory of Reasoned Action and Social Capital Theory. In SIGHCI 2013 Proceedings (p. 17). Retrieved from http://aisel.aisnet.org/sighci2013%0Ahttp://aisel.aisnet.org/sighci2013/17
48. Lin, X. & Hajli, M. (2013). Information Sharing on Social Networking Sites: the role of perceived control of information and gender. In Pre-ICIS Workshop on Information Security and Privacy (SIGSEC), 1–20.
49. Lin, X., Li, Y., Califf, C. B., & Featherman, M. (2013). Can social role theory explain gender differences in Facebook usage? In Proceedings of the Annual Hawaii International Conference on System Sciences (pp. 690–699). IEEE. https://doi.org/10.1109/HICSS.2013.125
50. Lin, X., Sarker, S., & Featherman, M. (2019). Users ’ Psychological Perceptions of Information Sharing in the Context of Social Media : A Comprehensive Model Users ’ Psychological Perceptions of Information. International Journal of Electronic Commerce, 23(4), 453–491. https://doi.org/10.1080/10864415.2019.1655210
51. Lin, X., & Wang, X. (2020). Examining gender differences in people’s information-sharing decisions on social networking sites. International Journal of Information Management, 50, 45–56. https://doi.org/10.1016/j.ijinfomgt.2019.05.004
52. Lu, H.-P., Chuan-Chuan Lin, J., Hsiao, K.-L., & Cheng, L.-T. (2010). Information sharing behaviour on blogs in Taiwan: Effects of interactivities and gender differences. Journal of Information Science, 36(3), 401–416. https://doi.org/10.1177/0165551510363631
53. Lyu, J., & Kim, J. (2020). Antecedents of Social Media–Induced Retail Commerce Activities: Impact of Brand–Consumer Relationships and Psychological Sense of Community. Journal of Interactive Advertising, 20(2), 119–132. https://doi.org/10.1080/15252019.2020.1769513
54. Magnuson, M. J., & Dundes, L. (2008). Gender Differences in “Social Portraits” Reflected in MySpace Profiles. CyberPsychology & Behavior, 11(2), 239–241. https://doi.org/10.1089/cpb.2007.0089
55. Marsden, P. V & Campbell, K. E. (1984). Measuring Tie Strength. Social Forces, 63(2), 482–501.
56. Riaz, M., & Sherani. (2021). Investigation of information sharing via multiple social media platforms: a comparison of Facebook and WeChat adoption. Quality and Quantity, 55(5), 1751–1773. https://doi.org/10.1007/s11135-020-01079-2
57. Ridings, C. M., & Gefen, D. (2006). Virtual Community Attraction: Why People Hang Out Online. Journal of Computer-Mediated Communication, 10(1), 00–00. https://doi.org/10.1111/j.1083-6101.2004.tb00229.x
58. Salehan, M., Kim, D. J., & Koo, C. (2018). A study of the effect of social trust, trust in social networking services, and sharing attitude, on two dimensions of personal information sharing behavior. The Journal of Supercomputing, 74(8), 3596–3619. https://doi.org/10.1007/s11227-016-1790-z
59. Sheikh, I., Ahmed, Y., Arabi Idid, S., Zeti, &, & Ahmad, A. (2018). News Consumption through SNS Platforms: Extended Motivational Model. © Media Watch, 9(1), 18–36. https://doi.org/10.15655/mw/2018/v9i1/49280
60. Social, W. are. (2020). Digital in 2020. Retrieved from https://wearesocial.com/digital-2020
61. Steffes, E. M., & Burgee, L. E. (2009). Social ties and online word of mouth. Internet Research, 19(1), 42–59. https://doi.org/10.1108/10662240910927812
62. Taylor, S., & Todd, P. (1995). Assessing IT Usage: The Role of Prior Experience. MIS Quarterly, 19(4), 561–570.
63. Trauth, E. M. (2013). The role of theory in gender and information systems research. Information and Organization, 23(4), 277–293.
64. Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 157–178.
65. Wang, X. W., Cao, Y. M., & Park, C. (2019). The relationships among community experience, community commitment, brand attitude, and purchase intention in social media. International Journal of Information Management, 49(October 2018), 475–488. https://doi.org/10.1016/j.ijinfomgt.2019.07.018
66. Yazıcıoğlu, Y. & Erdoğan: (2004). SPSS uygulamalı bilimsel araştırma yöntemleri. Ankara: Detay Anatolia Akademik Yayıncılık.
67. Zhang, L., Mattila, A. S., & Cranage, D. A. (2011). Become a Fan: A Conceptual Model for Social Media Marketing. In 16th Annual Graduate Education and Graduate Student Research Conference in Hospitality and Tourism (pp. 1–12).
68. Zhao, S. (2006). Do Internet Users Have More Social Ties? A Call for Differentiated Analyses of Internet Use. Journal of Computer-Mediated Communication, 11(3), 844–862. https://doi.org/10.1111/j.1083-6101.2006.00038.x