本研究之目的在探討Facebook使用者的自我特質對沉浸經驗與成癮間關係之模式驗證。本研究採用問卷調查法，研究對象是以使用過Facebook的使用者作為抽樣對象而抽樣的方式係採行非隨機抽樣當中的立意抽樣，扣除無效問卷後，有效問卷樣本為401份。
本研究以SPSS與AMOS統計套裝軟體進行資料處理分析。使用之統計方式包含描述性統計、項目分析、驗證性因素分析及結構方程模式(Structural Equation Modeling, SEM)。
本研究參酌學者專家之問卷作為本研究之工具，問卷調查後以統計軟體進行分析，並與文獻探討相對照作為討論之依據，並提出結論與建議作為後續研究者之參考。本研究主要發現如下：
一、 Facebook使用者的娛樂性對沉浸經驗無顯著的正向影響。
二、 Facebook使用者的專注力與互動性對沉浸經驗有顯著的正向影響。
三、 Facebook使用者的自我特質對沉浸經驗與社群成癮有顯著的正向影響，其中並以自我控制之子構面最為顯著。
四、 Facebook使用者的沉浸經驗對社群成癮有顯著的正向影響。

The purposes of the study were to explore the Facebook Flow Experience and Social networks Addiction Influenced by Users' Self-Traits. The study investigated user who has experience on Facebook, with Judgmental sample of quantitative research method, and after deducting invalid questionnaires the usable questionnaires were 430.
Adopting SPSS and AMOS, the present study analyzed the data via descriptive statistics, item analysis, confirmatory factor analysis (CFA), and structural equation modeling (SEM).
Drawing on the existing literature review, the questionnaires were administered via amelioration from those of renowned scholars and the collected data is analyzed through comparing with the literature review. Ultimately, conclusion and suggestions are proposed as the managerial strategic references for company managers.
The main research results are as follows:
1. Facebook users’ enjoyment is negatively significantly related to flow experience.
2. Facebook users’ concentration is positively significantly related to interactive and flow experience.
3. Facebook users’ self-trait is positively significantly related to flow experience and social networks addiction, and in which the sub-dimensions of the most remarkable self-control.
4. Facebook users’ flow experience is positively significantly related to social networks addiction.

一、 中文文獻
李怜妏(2011)。沉浸理論與網路成癮之社群網路服務線上遊戲探究-以臉書餐城為例(未出版之碩士論文)。世新大學，台北市。
黃雪甄(2011)。使用者的認知風格及知覺玩興對智慧型手機沉浸經驗與成癮之研究(未出版之碩士論文)。國立台灣師範大學，台北市。
資策會(2013)。討論區社群使用現況分析。上網日期：2013年11月23日，取自http://mic.iii.org.tw/aisp/reports/reportdetail2.asp?sesd=82738227&
docId=CDOC20130729002&doctype=RC&cate=&smode=1&countrypno=
資策會(2013)。網路社群於電腦與行動使用活動分析。上網日期：2013年7月29日，取自http://mic.iii.org.tw/aisp/reports/reportdetail2.asp?sesd=
436698900&docid=CDOC20130724012&doctype=RC&cate=&smode=1&countrypno=
資策會(2013)。網路社群於電腦與行動使用時間分析。上網日期：2013年5月27日，取自http://mic.iii.org.tw/aisp/reports/reportdetail2.asp?sesd=
436698900&docid=CDOC20130527001&doctype=RC&cate=&smode=1&countrypno=
資策會FIND網站Foreseeing Innovative New Digiservices (2013，10月)。2012年12月底止台灣上網人口。2013年10月14日取自http://ww
w.find.org.tw/find/home.aspx?page=many&id=359

二、 英文文獻
Ajzen, I. (1991). The theory of planned behavior. Organ. Behavior and Human Decision Processes. 50(2), 179-211.
Anderson, E. (1994). The code of the streets. Atlantic Monthly, 273, 81–94.
Amaral, L.A.N., Scala, A., Barthelemy, M., Stanley, H.E. (2000). Classes of small–world networks. Proceedings of the National Academy of Sciences, 97, 11149–11152.
Adamic, L.A., & Adar, E. (2003). Friends and neighbors on the web. Social Networks, 25(3), 211–230.
Aboujaoude, E., Koran, L. M., Gamel, N., Large, M. D., & Serpe, R. T. (2006). Potential markers for problematic internet use: A telephone survey of 2, 513 adults CNS spectrum. The Journal of Neuropsychiatric Medicine, 11, 750–755.
Ainley, M., Enger, L., Kennedy, G. (2007). The elusive experience of ‘flow’: qualitative and quantitative indicators. International Journal of Educational Research, 4(2), 109–121.
American Psychiatric Association. (2012). R 40 internet use disorder. DSM-5 development.(07.09.2012)<http://www.dsm5.org/ProposedRevision/Pages/proposedrevision.aspx?rid=573#>.
Alexa (2013) Alexa Top Sites. http://www.alexa.com/topsites, accessed June, 2013.
Barnes, J.A. (1954). Class and committees in a Norwegian Island Parish. Human Relations, 7, 39–58.
Bentler, P.M. (1980). Multivariate analysis with latent variables: Causal modeling. Annual review of psychology, 31(1), 419-456.
Bandura, A. (1982). Self-efficacy mechanism in human agency. Amer. Psychologist. 37(2), 122-147.
Bagozzi, R.P. and Yi, Y. (1988). On the Evaluation of Structural Equation Mdels. Academy of Marking Science, 16, 76-94.
Bollen, K.A. (1989). Structural equations with latent variables. New York: Wiley.
Brown, J.D. (1993). Motivation conflict and the self: the double-bind of low self-esteem. in Baumeister, R.F. (Ed.): The Puzzle of Low Self-Regard, Plenum, New York, NY, pp.117–130.
Blaine, B., & Crocker, J. (1993). Self-esteem and self-serving biases in reactions to positive and negative events: an integrative view, in Baumeister, R.F. (Ed.): Self-Esteem: The Puzzle of Low Self-Regard, Plenum, New York, pp.219–241.
Bentler, P. M. (1995). EQS structural equations program manual: Multivariate Software.
Baumeister, R., Smart, L., & Boden, J.M. (1996) ‘Relation of threatened egotism to violence and aggression: the dark side of high self-esteem’, Psychological Review, 103, 5–33.
Bandura, A. (1997). Self-efficacy: The Exercise of Control, Freeman, New York.
Bandura, A. (1999). Self-efficacy: toward a unifying theory of behavioral change, in Baumeister, R.F. (Ed.): The Self in Social Psychology, Psychology Press, Philadelphia, pp.285–298.
Bruning, R., Schraw, G., & Ronning, R. (1999). Cognitive Psychology and Instruction, Merrill, New Jersey.
Baumeister, R.F. (Ed.) (1999) The nature and structure of the self: an overview, The Self in Social Psychology, Psychology Press, Philadelphia, pp.1–20.
Beard, K. W., & Wolf, E. M. (2001). Modification in the proposed diagnostic criteria for internet Addiction. Cyberpsychology & Behavior, 4, 377–383. doi:10.1089/109493101300210286.
Beard, K. (2005). Internet Addiction: A review of current assessment techniques and potential assessment questions. CyberPsychology and Behavior, 8(1), 7–14.
Brown, T.A. (2006). Confirmatory factor analysis for applied research: Guilford Press.
Boyd, D. M., & Ellison, N. B. (2007). Social Network Sites: Definition, History, and Scholarship. Journal of Computer-Mediated Communication, 13(1), 210-230. doi:10.1111/j.1083-6101.2007.00393.x
Block, J. J. (2007). Pathological computer use in the USA, in 2007 international symposium on the counseling and treatment of youth internet Addiction. Seoul, Korea, National Youth Commission, p 433.
Block, J. J. (2008). Issues for DSM-V: Internet Addiction. American Journal of Psychiatry, 165, 306–307.
Bridges, E., Renee, F. (2008). “Hedonic and Utilitarian Shopping Goals: The Online Experience,” Journal of Business Research, 61(4), 309–314.
Barker, V. (2009). Older adolescents' motivations for social network site use: The influence of gender, group identity, and collective self-esteem. CyberPsychology & Behavior, 12, 209-213.
Byrne, B.B. (2010). Principles and Practice of Structural Equation Modeling: Guilford Press, New York, NY.
Cureton, E. E. (1957). The upper and lower twenty-seven per cent rule. Psychometrika, 22(3), 293-296.
Csikszentmihalyi, M. (1975), Beyond Boredom and Anxiety, Jossey-Bass, San Francisco, CA.
Campbell, A., Converse, P.E., & Rodgers, W.L. (1976). The Quality of American Life: Perceptions, Evaluations, and Satisfactions, Russel Sage, New York, NY.
Carmines, E.G., & McIver, J.P. (1981). Analyzing models with unobserved variables: Analysis of covariance structures. Social measurement: Current issues, 65-115.
Csikszentmihalyi, M., & Getzels, J.W. (1988) Creativity and problem finding. In F.G. Farley and R.W. Heperud (Eds). The Foundations of Aesthetics, Art, and Art Education. New York: Praeger. (pp. 91–106).
Campbell, J.D. (1990). Self-esteem and clarity of the self-concept. Journal of Personality and Social Psychology, 59, 473–505.
Csikszentmihalyi, Mihaly (1990), Flow: The Psychology of Optimal Experience,New York: Harper and Row.
Campbell, J. D., & Lavallee, L. F. (1993). Who am I? The role of self-concept confusion in understanding the behavior of people with low self-esteem, in Baumeister, R.F. (Ed.): The Self in Social Psychology, Psychology Press, Philadelphia, PA, pp.3–20.
Clarke, S. G., & Haworth, J. T. (1994). Flow Experience in the Daily Lives of 6th-Form College-Students. British Journal of Psychology, 85, 511-523.
Craig, R.J. (1995). The role of personality in understanding substance abuse. Alcoholism Treatment Quarterly, 13, 17–27.
Cervone, D. (2000). Thinking about self-efficacy. Behavior Modification, 24 (1), 30-56. doi: 10.11 77/0145445500241002
Csikszentmihalyi, M. (2000). The contribution of flow to positive psychology. In M. E. P. Seligman and J. Gillham (Eds.), The science of optimism and hope (pp. 387–395). Philadelphia: Templeton Foundation Press.
Chen, H., Wigand, R. T., Nilan , M. (2000) "Exploring Web users’ optimal flow experiences", Information Technology & People, 13( 4), 263 – 281.
Cattell, V. (2001). Poor people, poor places, and poor health: the mediating role of social networks and social capital. Social Science & Medicine, 52(10), 1501–1516.
Caplan, S. E. (2002). Problematic Internet Use and Psychosocial Well-being Development of A Theory-Based Cognitive-Behavioral Measurement Instrument, Computers in Human Behavior, 18(5) , 553-575.
Cao, F., & Su, L. (2006). Internet addiction among Chinese adolescents: prevalence and psychological features. Child: Care, Health and Development, 33(3), 275–281.
Caplan, S. E. (2007). Relations Among Loneliness, Social Anxiety, and Problematic Internet Use. CyberPsychology and Behavior, 10(2), 234-242.
Choi, D. H., Kim, J., & Kim, S. H. (2007). ERP Training With a Web-Based Electronic Learning System: The Flow Theory Perspective. International Journal of Human-Computer Studies, 65, 223–243.
Chiu, P.Y., Cheung, C. M. K. Lee, & M. K. O. (2008). Online Social Networks: Why Do “We” Use Facebook?, In Proceedings of the First World Summit on the Knowledge Society, Communications in Computer and Information Science, 19, 67–74.
Caplan, S. E. (2010). Theory and measurement of generalized problematic Internet use: A two-step approach. Computers in Human Behavior, 26, 1089–1097.
Chang, Y. P., & Zhu, D. H. (2012). The role of perceived social capital and flow experience in building users’ continuance intention to social networking sites in China. Computers in Human Behavior, 28, 995-1001.
Chang, C. C. (2013). Examining users’ intention to continue using social network games: A flow experience perspective. Telematics and Informatics, 30(4), 311-321.
Checkfacebook(2013).http://www.socialbakers.com/facebook-overview-statistics/, accessed June, 2013.
Doll, W.J., Xia, W., & Torkzadeh, G. (1994). A confirmatory factor analysis of the end-user computing satisfaction instrument. MIS Quarterly, 453-461.
Daft, R. L., & Lengel, R. H. (1986). Organizational information requirements media richness and structural design. Management Science, 32(5), 554–571.
Ducoffe, R. H. (1996). Advertising value and advertising on the web. Journal of Advertising Research, 36(5), 21 – 35.
Davis, R., Flett, G., & Besser, A. (2002). Validation of a new scale for measuring problematic Internet use: Implications for preemployment screening. CyberPsychology and Behavior, 5(4), 331–345.
Dell’Osso, B., Altamura, A. C., Allen, A., Marazziti, D., & Hollander, E. (2006). Epidemiologic and clinical updates on impulse control disorders: A critical review. Clinical Neuroscience (New York, NY), 256, 464–475.
Douglas, A. C., Mills, J. E., Niang, M., Stepchenkova, S., Byun, S., Ruffini, C., Lee, S. K., Loutfi, J., Lee, J. K. Atallah, M., & Blanton, M. (2008). Internet Addiction: Meta-synthesis of qualitative research for the decade 1996–2006. Computers in Human Behavior, 24, 3027-3044.
Dimicco, J., Millen, D.R., Geyer, W., Dugan, C., Brownholtz, B., Muller M. (2008). Motivations for Social Networking at Work, In Proceedings of the Computer Supported Cooperative Work 2008 Conference, ACM Digital Library, pp. 711–720.
Demetrovics, Z., Szeredi, B., & Rozsa, S. (2008). The three-factor model of Internet Addiction: The development of the Problematic Internet Use Questionnaire. Behavior Research Methods, 40(2), 563-574. doi: 10.3758/BRM.40.2.563
Esteban-Millat, I., Martínez-López, F. J., Huertas-García, R., Meseguer, A., Rodríguez-Ardura, I.(2014). Modelling students’ flow experiences in an online learning environment. Computers & Education, 71, 111-123.
Echeburua, E., & de Corral, P. (2010). Addiction to new technologies and to online social networking in young people: a new challenge. Adicciones, 22, 91–95.
Fornell, C., & Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 39-50.
Fan, X., Thompson, B., & Wang, L. (1999). Effects of sample size, estimation methods, and model specification on structural equation modeling fit indexes. Structural Equation Modeling.A Multidisciplinary Journal, 6(1), 56-83.
Flake, G., Lawrence, S., & Lee Giles, C. (2000). Efficient identification of web communities, In Proceedings of the Sixth ACM Conference on Knowledge Discovery and Data Mining, pp. 150–160.
Fortin, D. R., & Dholakia, R. R. (2000). The impact of interactivity and vividness on involvement: an empirical test of the Hoffman–Novak model. Presentation at the INFORMS Conference on Understanding Consumer Behavior on the Internet, Los Angeles.
Fogei, J. & Nehmad, E., (2009). internet social network communities: Risk taking, trust, and privacy concerns. Computers in Human Behavior, 25, 153-160.
Facebook (2013). Company timeline. Retrieved from Retrieved December 20, 2013, from: http://www.Facebook.com/press/info.php?timeline
Facebook (2013). Facebook reports third quarter 2013 results, Retrieved from http://investor.fb.com/releasedetail.cfm?ReleaseID=802760
Ghani, J. A., Supnick, R., Rooney, P. (1991). The experience of flow in computer-mediated and in face-to-face groups. J. I. DeGross, I. Benbasat, G. DeSanctis, and C. M. Beath, eds. Proc. 12th Internat. Conf. Inform. System, New York, 229-237.
Gist, M.E. & Mitchell, T.R. (1992). Self-efficacy: a theoretical analysis of its determinants and malleability. The Academy of Management Review, 17, 183–211.
Ghani, J. A., & Deshpande, S. P. (1994). Task characteristics and the experience of optimal flow in human–computer interaction. The Journal of Psychology, 128(4), 381–389.
Goldberg, I. (1995). Internet Addictive disorder (IAD) diagnostic criteria. <http://www.psycom.net/iadcriteria.html>.
Goldberg, I. (1996). Internet Addiction disorder. [On-Line] Available at http://www.physics.wisc.edu/ ~ shalizi/internet Addiction criteria.html.
Griffiths, M. (1998). Internet Addiction: does it really exist. In J. Gackenbach, Psychology and the Internet: intrapersonal, interpersonal, and transpersonal implications. New York: Academic Press.
Greenfield, D. (1999). Virtual Addiction: Help for Netheads, Cyberfreaks, and those who love them. Oakland, CA: New Harbinger.
Griffiths, M. (2000). Internet Addiction– Time to be taken seriously? Addiction Research, 8(5), 413–418.
Golbeck, J. (2005). Computing and Applying Trust inWeb-Based Social Networks, Dissertation Submitted to the Faculty of the Graduate School of th Universtity of Maryland, College Park in partial fulfilment of the requirements for the degree of Doctor of Philosophy.
Gefen, D. and Straub, D.W. (2005). A practical guide to factorial validity using PLS-Graph: tutorial and annotated example. Communications of AIS, 16 (1), 91-109.
Golbeck, J., & Hendler, J. (2006). FilmTrust: movie recommendations using trust in web-based social networks, In Proceedings of Consumer Communications and Networking Conference, IEEE Conference Proceedings 1, 282–286.
Griffiths, M.D. (2009). The psychology of addictive behaviour. In: Cardwell, M., Clark, M.L., Meldrum, C., Waddely, A. (Eds.), Psychology for A2 Level. Harper 419 Collins, London, pp. 436–471.
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis (5th ed.). New York: Macmillan.
Hu, L., & Bentler, P.M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55.
Haythornthwaite, C. (2005). Social networks and Internet connectivity effects. Information, Communication, & Society, 8(2), 125–147.
Hur, M. (2006). Demographic, habitual, and socioeconomic determinants of Internet Addiction disorder: An empirical study of Korean teenagers. CyberPsychology and Behavior, 9(5), 514–525.
Hollander, E., Stein, D. J. (Eds.). (2006). Clinical manual of impulse-control disorders. Arlington, VA: American Psychiatric.
Hyun, C. D., Kim, J., Kim, S. H. (2007), “ERP Training With a Web-Based Electronic Learning System: The Flow Theory Perspective,” International Journal of Human-Computer Studies, 65, 223–243.
Howard, B. (2008) Analyzing online social networks. Communications of the ACM, 51(11), 14–16.
Hoffman, D. L., Novak, T. P. (2009). Flow Online: Lessons Learned and Future Prospects, Journal of Interactive Marketing, 23, 23-34.
Hair, J., Black, B., Babin, B., Anderson, R.E., & Tatham, R.L. (2009). Multivariate Data Analysis (7 ed.): Prentice Hall.
Huberman, B.A., Romero, D.M., & Wu, F. (2009). Social networks that matter: Twitter under the microscope. First Monday, 14(1), 1-8.
Huang, X., Zhang, H., Li, M., Wang, J., Zhang, Y., & Tao, R. (2010). Mental health, personality, and parental rearing styles of adolescents with internet addiction disorder. Cyberpsychology, Behavior, and Social Networking, 13(4), 401–406.
Hong, J. C., Hwang, M. Y., Chen, W. C., Lee, C. C., Lin, P. S., Chen, Y. L. (2013). Comparing the retention and flow experience in playing Solitary and Heart Attack games of San Zi Jing: A perspective of Dual Process Theory. Computers & Education, 69, 369-376.
Jankowski, M.S. (1991) Islands in the Street: Gangs and American Urban Society, University of California Press, Berkeley, CA.
Joreskog, K.G., & Sorbom, D. (1983). LISREL: Analysis of linear structural relations by the method of maximum likelihood, versions V and VI. Chicago: National Education Resources.
Joreskog, K.G., & Sorbom, D. (1984). LISREL VI: Analysis of linear structural relationships by the method of maximum likelihood.Mooresville, IN: Scientific Software: Inc.
Jeiicic, H., Bobek, D.L., Pheips, E., Lerner, R.M., & Lerner, J.V. (2007). Using positive youth deveiopment to predict contribution and risk behaviors in eariy adoiescence: Findings from the first two waves of the 4-H Study of Positve Youth Deveiopment. Internationai Journal of Behavioral Development, 31, 263-273.
Jackson, D.L, Gillaspy-Jr, J.A., & Purc-Stephenson, R. (2009). Reporting practices in confirmatory factor analysis:An overview and some recommendations. Psychological methods, 14(1), 6-23.
Joo, Y. J., Lim, K. Y., & Kim, S. M. (2012). A model for predicting learning flow and achievement in corporate e-learning. Educational Technology & Society, 15(1), 313–325.
Jap, T., Tiatri, S., Jaya, E. S., & Suteja, M. S. (2013). The Development of Indonesian Online Game Addiction Questionnaire. PLoS ONE, 8(4): e61098. doi:10.1371/journal.pone.0061098
Kelley, T.L. (1939). The selection of upper and lower groups for the validation of test items. Journal of Educational Psychology, 30(1), 17.
Kernis, M. (1993) ‘The roles of stability and level of self-esteem in psychological functioning’, in Baumeister, R.F. (Ed.): Self-esteem: The Puzzle of Low Self-Regard, Plenum, New York, NY, 167–182.
Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205-223.
Kline, RB. (2005). Principles and practice of structural equation modeling Guilford. New York, 366.
Kim, B. (2006). An exploratory study of an excessive reliance on digital devices. KADO Issue Report, 30(3), 1-36.
Kim, K., Ryu, E., Chon, M.Y., Yeun, E.J., Choi, S.Y., Seo, J.S., & Nam, B.W. (2006). Internet addiction in Korean adolescents and its relation to depression and suicidal ideation: a questionnaire survey. International Journal of Nursing Studies, 43, 185–192.
Kenny, D. A. (2006). Confirmatory factor analysis for applied research (T. A. Brown Ed.). New York: Guilford.
Kim, E.J., Namkoong, K., Ku, T., & Kim, S.J. (2008). The relationship between online game addiction and aggression, self-control and narcissistic personality traits. European Psychiatry, 23, 212–218.
Kim, Y., & Park, S. (2007a). A study on the effects of on-line game on gamers’ flow experience and loyalty. Korean Journal of Broadcasting and Telecommunication Studies, 21(2), 179-208.
Kim, Y., & Park, S. (2007b). A study on the online game use influences in game flow and Addiction: Focusing on the uses and gratifications approach. Korean Journal of Journalism and Communication Studies, 51(1), 355-377.
Kim, H.-K., & Davis, K. E. (2009). Toward a comprehensive theory of problematic Internet use: Evaluating the role of self-esteem, anxiety, flow, and the self-rated importance of Internet activities. Computers in Human Behavior, 25, 490–500.
Kazienko, P. (2007). Expansion of Telecommunication Social Networks, In Proceedings of the fourth International Conference on Cooperative Design, Visualization and Engineering, Springer Verlag. Lecture Notes in Computer Science, 4674, 404–412.
Kazienko, P., Musiał, K., & Zgrzywa, A. (2009). Evaluation of node position based on email communication. Control and Cybernetics, 38(1), 67–86.
Krischner, P., Karpinski, A. (2010). Facebook and academic performance. Computer in Human Behavior. 26, 1237–1245.
Karaiskos, D., Tzaveiias, E., Baita, G., & Paparrigopoulos, T, (2010). Sociai network addiction: A new ciinicai disorder? European Psychiatry, 25, 855.
Kuss, D.J., Griffiths, M.D. (2011b). Online social networking and addiction—a review of the psychological literature. International Journal of Environmental Research and Public Health, 8, 3528–3552.
Kazienko, P., Musiał, K., & Kajdanowicz, T. (2011). Multidimensional social network and its application to the social recommender system. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 41(4), 746–759.
Khang, H., Woo, H. J., & Kim, J. K. (2012). Self as an antecedent of mobile phone Addiction. International Journal of Mobile Communications, 10(1), 65-84.
Khang, H., Kim, K. J., & Kim, Y. (2013). Self-traits and motivations as antecedents of digital media flow and Addiction: The Internet, mobile phones, and video games. Computers in Human Behavior, 29, 2416-2424.
Long, D.E. (1990). The Anatomy of Terrorism. Free Press, New York, NY.
Louge, A.W. (1995). Self-Control: Waiting Until Tomorrow for What You Want Today, Prentice Hall, NJ.
Lesieur, H. R., & Blume, S. B. (1993). Revising the South Oaks Gambling Screen in different settings. Journal of Gambling Studies, 9, 213–223.
Lazega, E. (2001). The Collegial Phenomenon. The Social Mechanism Of Co–Operation Among Peers In A Corporate Law Partnership. Oxford University Press, Oxford.
Luna, D., Peracchio, L. A., & de Juan, M. D. (2002). Cross-cultural and cognitive aspects of web site navigation. Journal of the Academy of Marketing Science , 30(4), 397 – 410.
Lee, Y., & Kim, S. (2005). Reliability and validity for self-control measurement scales. Theory and Practice of Education, 10, 29–51.
Leskovec, J., Backstrom, L., Kumar, R., & Tomkins, A. (2008) Microscopic evolution of social networks, In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM, 462–470.
La Barbera, D., La Pagiia, F. & Vaisavoia, R. (2009). Sociai Network and Addiction. Cyberpsychoiogy & Behavior, 12, 628-629.
Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabasi, A.L., Brewer, D., Christakis, N., Contractor, N., Fowler, J., Gutmann, M., Jebara, T., King, G., Macy, M., Roy, D., & Van Alstyne, M. (2009). Life in the network: the coming age of computational social science. Science, 323(5915), 721–723.
Lu, Y. B., Zhou, T., & Wang, B. (2009). Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Computers in Human Behavior, 25(1), 29-39. doi: http://dx.doi.org/10.1016/j.chb.2008.06.002
Mehrabian , A., Russell, J.A. (1974).An Approach to Environmental Psychology. MIT Press, Cambridge, MA.
Montgomery, J. (1991). Social networks and labor-market outcomes: toward an economic analysis. American Economic Review, 81(5), 1407–1418.
Mruk, C. (1995). Self-Esteem: Research, Theory, and Practice, Springer Publishing, New York, NY.
Maibach, E., & Murphy, D. A. (1995). Self-efficacy in health promotion research and practice: conceptualization and measurement. Health Education Research, 10(1), 7-50.
Moneta, G. B., & Csikszentmihalyi, M. (1996). The effect of perceived challenges and skills on the quality of subjective experience. Journal of Personality, 64, 274–310. doi:10.1111/j.1467-6494.1996.tb00512.x.
Morris, M. (1997). Sexual network and HIV. AIDS, 11, 209–216.
MacCallum, R.C., Browne, M.W., & Sugawara, H.M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological methods, 1(2), 130.
Marsh, H.W., Balla, J.R., & Hau, K. (1996). An evaluation of incremental fit indices: A clarification of mathematical and empirical properties. Advanced structural equation modelling. Issues and techniques, 315-354.
MacCallum, R.C., & Hong, S. (1997). Power analysis in covariance structure modeling using GFI and AGFI. Multivariate Behavioral Research, 32(2), 193-210.
Morahan-Martin, J., & Schumacher, P. (2000). Incidence and correlates of pathological Internet use among college students. Computers in Human Behavior, 16, 113–129.
MacCallum, R.C., & Austin, J.T. (2000). Applications of structural equation modeling in psychological research. Annual review of psychology, 51(1), 201-226.
McDonald, R.P., & Ho, M.R. (2002). Principles and practice in reporting structural equation analyses. Psychological methods, 7(1), 64-82.
Mulaik, S.A. (2009). Linear causal modeling with structural equations, Chapman & Hall/CRC.Multivariate Data Analysis (6th ed.). New York: Macmillan.
Musiał, K., Kazienko, P. (2013). Social networks on the Internet. World Wide Web, 16(1), 31-72.
Novak, T. P. & Hoffman, D. L.(1997). Modeling the Structure of the Flow Experience among Web Users. INFORMS Marketing Science and the Internet Mini-Conference.
Novak, T. P., Hoffman, D. L., & Yung, Y. F. (1998). Modeling the structure of the flow experience among Web users. INFORMS Marketing Science and the Internet Mini-Conference MIT.
Novak, T. P., Hoffman, D., & Yung, Y. (2000). Measuring the customer experience in online environments: a ssructural modeling approach. Marketing Science 19 (Winter), 22–42.
Nyikos, E., Szeredi, B., & Demetrovics, Z. (2001). Egy uj viselkedeses Addikcio: AzInternethasznalat szemelyisegpszichologiai korrelatumai [A new behavioral Addiction: The personality psychological correlates of Internet use]. Pszichoterapia, 10, 168–182
Newman, M.E.J. (2001). The structure of scientific collaboration networks, In Proceedings of the National Academy of Sciences of the United States of America, 98, 404–409.
Orzack, M. (1999). Computer Addiction: Is it real or is it virtual? The Harvard Mental Health Letter, 15, 8.
Ozcan, N. K., Buzlu, S.(2007). Internet Use and Its Relationships with Psychosocial Situation for a sample of University Students, CyberPsychology and Behavior, 10( 6), 767-772.
Pagel, M., Erdly, W., & Becker, J. (1987). Social networks: we get by with (and in spite of) a little help from our friends. Journal of Personality and Social Psychology, 53(4), 793–804.
Pace, S. (2004) "A Grounded Theory of the Flow Experiences of Web Users," International Journal of Human-Computer Studies, 60(3), 327-363.
Pearce, J. M., Ainley, M., & Howard, S. (2005). The ebb and flow of online learning. Computers in Human Behavior, 21(5), 745–771.
Peliing, E.L. & White, K.M. (2009). The theory of pianned behavior appiied to young peopie's use of sociai networkting web sites. CyberPsychology & Behavior, 12, 755-759.
Park, S. B., & Hwang, H. S. (2009). Understanding Online Game Addiction: Connection between Presence and Flow. Human-Computer Interaction, 5613, 378-386. dol:10.1007/978-3-642-02583-9_42
Mathwick, C. and Rigdon, E. (2004). Play, Flow, and the Online Search Experience. Journal of Consumer Research, 31 (2), 324-332.
Marie-Odile, R., Chandra, R. (2005). A Model of Consumer Web Navigational Behavior: Conceptual Development and Application, Journal of Business Research, 58, 1019–1029.
Rosenberg, M. (1965) Society and Adolescent Self-Image, Princeton University, Princeton, NJ.
Renzetti, C.M. (1992). Violent Betrayal: Partner Abuse in Lesbian Relationships, Sage, Newbury Park, CA.
Robins, G.L., Alexander, M. (2004). Small Worlds Among Interlocking Directors: Network Structure and Distance in Bipartite Graphs, Computational & Mathematical Organization Theory 10, 1, Kluwer Academic Publisher, 69–94.
Richard, M.O., & Chandra, R. (2005). A Model of Consumer Web Navigational Behavior: Conceptual Development and Application. Journal of Business Research, 58, 1019–1029.
Rice, M. (2005). Online Addiction. Beijing Review, 48(46), 32–33.
Rossin, D., Ro, Y. K., Klein, B. D., & Guo, Y. M. (2009). The effects of flow on learning outcomes in an online information management course. Journal of Information Systems Education, 20(1), 87–98.
Roccas, S., Sagiv, L., Oppenheim, S., Elster, A., & Gal, A. (2013). Integrating Content and Structure Aspects of the Self:Traits,Values, and Self-Improvement. Journal of Personality, Advance online publication. doi: 10.1111/jopy.12041
Steuer, J. (1992). Defining virtual reality: dimensions determining telepresence. Journal of Communication, 42(4), 73–93.
Shapira, N. A., Goldsmith, T. G., Keck, P. E., Jr., Khosla, U. M., & McElroy, S. L. (2000). Psychiatric features of individuals with problematic internet use. Journal of Affective Disorders, 57, 267–272.
Scholz, U., Dona, B. G., Sud, S., & Schwarzer, R. (2002). Is general self-efficacy a universal construct? Psychometric findings from 25 countries. European Journal of Psychological Assessment, 18(3), 242-251.
Schonlau, M. Zapert, K., Simon, L. P., Sanstad, K., Marcus, S., Adams, J., Kan, H., Turner, R., & Berry, S. (2003). A comparison between responses from a propensity-weighted web survey and an identical RDD survey. Social Science Computer Review, 21(10): 1-11.
Schumacker, R.E., & Lomax, R.G. (2004). A beginner's guide to structural equation modeling(Vol. 1): Lawrence Erlbaum.
Skadberg, Y. X., & Kimmel, J. R. (2004). Visitors’ flow experience while browsing a Web site: its measurement, contributing factors and consequences. Computers in Human Behavior, 20, 403-422.
Schumacker, R.E., & Lomax, R.G. (2004). A beginner's guide to structural equation modeling(Vol. 1): Lawrence Erlbaum.
Siekpe, J.S. (2005) An examination of the multidimensionality of flow construct in a computer-mediated environment. Journal of Electronic Commerce Research, 6, 31–43.
Schreiber, J.B, Nora, A., Stage, F.K., Barlow, E.A.,& King, J. (2006). Reporting structural equation modeling and confirmatory factor analysis results: A review. The Journal of Educational Research, 99(6), 323-338.
Sanchez-Franco, M. J. (2006), “Exploring the Influence of Gender on Web Usage Via Partial Least Squares,” Behavior and Information Technology, 25 (1), 19–36.
Shin, N. (2006). Online Learner's Flow Experience: An Empirical Study. British Journal of Educational Technology, 37 (5), 705–720.
Schreiber, J.B. (2008). Core reporting practices in structural equation modeling. Research in Social and Administrative Pharmacy, 4(2), 83-97.
Sledgianowska, D.S., & Kulviwat, S. (2009). Using social network sites: the effects of playfulness, critical mass and trust in a hedonic context. Journal of Computer Information Systems, 49, 74-83.
Trevino, L. K. & Webster, J. (1992). Flow in Computer-Mediated Communication: Electronic Mail and Voice Mail Evaluation and Impacts. Communication Research, 19(5), 539-573.
Torkzadeh, G., Koufteros, X., & Pflughoeft, K. (2003). Confirmatory analysis of computer self-efficacy. Structural Equation Modeling, 10(2), 263-275.
Thompson, B. (2004). Exploratory and confirmatory factor analysis: Understanding concepts and applications: American Psychological Association.
Tangney, J. P, Baumeister, R.F., & Boone, A. L. (2004). High self-control predicts good adjustment, less pathology, better grades, and interpersonal success. Journal of Personality, 72, 271–324.
Thatcher, A., & Goolam, S. (2005). Development and psychometric properties of the Problematic Internet Use Questionnaire. South African Journal of Psychology, 35, 793–809.
Tone, H. J., Zhao, H. R., & Yan, W. S. (2014). The attraction of online games: An important factor for Internet Addiction. Computers in Human Behavior, 30, 321-327.
Ullman, J.B., Tabachnick, B.G., & Fidell, L.S. (2001). Using multivariate statistics. Using multivariate statistics.
Ullén, F., Manzano, Ö. D., Almeida, R., Magnusson, P. K. E., Pedersen, N.L., Nakamura, J., Csíkszentmihályi, M., & Madison, G. (2012). Proneness for psychological flow in everyday life: Associations with personality and intelligence. Personality and Individual Differences, 52, 167-172.
Webster, J., & Martocchio, J. J. (1992). Microcomputer playfulness: Development of a measure with workplace implications. MIS Quarterly, 201–226.
Webster, J., Trevino, L.K., & Ryan, L. (1993). The Dimensionality and Correlates of Flow in Human Computer Interactions. Computers in Human Behavior, 9(4), 411-426.
Wellman, B., Salaff, J., Dimitrova, D., Garton, L., Gulia,M., & Haythornthwaite, C. (1996). Computer networks as social networks: collaborative work, telework, and virtual community. Annual Review of Sociology, 22(1), 213–238.
Widyanto, L., & Griffiths, M. (2006). Internet Addiction: A critical review. International Journal of Mental Health and Addiction,4(1), 31–51.
Wiison, K., Fornasier, S. & White, K.M., (2010). Psychoiogicai predictors of young adults' use of social networking sites. Cyberpsychoiogy, Behavior and Sociai Networking, 13, 173-177.
Wanga, L. C., & Hsiao, D. F. (2012). Antecedents of flow in retail store shopping. Journal of Retailing and Consumer Services, 19, 381-389.
Xia, S. Y., Kimmel, J. R. (2004), “Visitors' Flow Experience While Browsing a Web Site: Its Measurement, Contributing Factors and Consequences,” Computers in Human Behavior, 20, 403–422.
Young, K. S. (1996). Internet Addiction: The emergence of a new clinical disorder. Paper presented at the 104th annual meeting of the American Psychological Association, August 11, 1996. Toronto, Canada.
Young, K. S.(1998). Internet Addiction: The emergence of a new clinical disorder. CyberPsychology and Behavior, 1(3), 237–244.
Young, K. S. (1999). Internet Addiction: Symptoms, evaluation, and treatment. In L. Van de Creek & T. Jackson (Eds.), Innovations in clinical practice. A source book, 17 (pp. 19–31). Sarasota, FL: Professional Resource Press.
Yea, J., & Kim, D. (2003). Effects of the internet uses and gratifications, flow, and dispositional orientation on the internet Addiction. Korean Journal of Consumer Studies, 14, 45–83.
Young, K. S. (2004). Internet Addiction: The consequences of a new clinical phenomena. In K. Doyle (Ed.), Psychology and the new media (pp. 1–14). Thousand Oaks, CA: Am. Behavioral Scientist.
Yang, W.S., Dia, J.B., Cheng, H.CH., & Lin, H.T. (2006). Mining Social Networks for Targeted Advertising, In Proceedings of the 39th Hawaii International Conference on Systems Science, 6, IEEE Computer Society, 137a.
Zimmerman, B. J. (2000). Self-efficacy: an essential motive to learn, Contemporary Educational Psychology, 25, 82–91.
Zhou, S.X. (2010). Gratifications, ioneiiness, ieisure boredom and seif-esteem as predictors of SNS-game addiction and usage pattern among Chinese coilege students, in Chinese University of Hong Kong: Hong Kong. Located at: http://www.com.cuhk.edu.hk/courses/ pgp_nm/projects/2010/Seiina%20Zhou_Finai.pdf