請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/57104完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 李瑞庭(Anthony J. T. Lee) | |
| dc.contributor.author | Wan-Hsin Tang | en |
| dc.contributor.author | 唐婉馨 | zh_TW |
| dc.date.accessioned | 2021-06-16T06:35:02Z | - |
| dc.date.available | 2014-08-21 | |
| dc.date.copyright | 2014-08-21 | |
| dc.date.issued | 2014 | |
| dc.date.submitted | 2014-08-02 | |
| dc.identifier.citation | [1] S. Asur and B.A. Huberman, 'Predicting the future with social media', in Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01. 2010, IEEE Computer Society. p. 492-499.
[2] B.A. Austin, 'Immediate seating: A look at movie audiences'. 1989: Wadsworth Publishing Company Belmont, CA. [3] E. Bakshy, J.M. Hofman, W.A. Mason, and D.J. Watts, 'Everyone's an influencer: Quantifying influence on Twitter', in Proceedings of the Fourth ACM International Conference on Web Search and Data Mining. 2011, ACM: Hong Kong, China. p. 65-74. [4] B.L. Bayus, 'Word of mouth: The indirect effects of marketing efforts'. Journal of Advertising Research, 1985. 25(3): p. 31-39. [5] M. Cha, H. Haddadi, F. Benevenuto, and P.K. Gummadi. 'Measuring user influence in Twitter: The million follower fallacy'. in Proceedings of the Third AAAI International Conference on Weblogs and Social Media. 2010. [6] J.A. Chevalier and D. Mayzlin, 'The effect of word of mouth on sales: Online book reviews'. Journal of Marketing Research, 2006. 43(3): p. 345-354. [7] P.K. Chintagunta, S. Gopinath, and S. Venkataraman, 'The effects of online user reviews on movie box office performance: Accounting for sequential rollout and aggregation across local markets'. Marketing Science, 2010. 29(5): p. 944-957. [8] W. Duan, B. Gu, and A.B. Whinston, 'The dynamics of online word-of-mouth and product sales—An empirical investigation of the movie industry'. Journal of Retailing, 2008. 84(2): p. 233-242. [9] A. Elberse and J. Eliashberg, 'Demand and supply dynamics for sequentially released products in international markets: The case of motion pictures'. Marketing Science, 2003. 22(3): p. 329-354. [10] R.J. Faber and T.C. O'Guinn, 'Effect of media advertising and other sources on movie selection'. Journalism Quarterly, 1984. 61(2): p. 371-77. [11] B.J. Frey and D. Dueck, 'Clustering by passing messages between data points'. Science, 2007. 315(5814): p. 972-976. [12] J. Goldenberg, B. Libai, and E. Muller, 'Talk of the network: A complex systems look at the underlying process of word-of-mouth'. Marketing Letters, 2001. 12(3): p. 211-223. [13] M. Granovetter, 'Threshold models of collective behavior'. American Journal of Sociology, 1978: p. 1420-1443. [14] T. Iwata, A. Shah, and Z. Ghahramani. 'Discovering latent influence in online social activities via shared cascade poisson processes'. in Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2013. ACM. [15] J.M. Jones and C.J. Ritz, 'Incorporating distribution into new product diffusion models'. International Journal of Research in Marketing, 1991. 8(2): p. 91-112. [16] M. Joshi, D. Das, K. Gimpel, and N.A. Smith, 'Movie reviews and revenues: an experiment in text regression', in Proceedings of Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics. 2010, Association for Computational Linguistics: Los Angeles, California. p. 293-296. [17] D. Kempe, J. Kleinberg, #201, and v. Tardos, 'Maximizing the spread of influence through a social network', in Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2003, ACM: Washington, D.C. p. 137-146. [18] S. Kullback and R.A. Leibler, 'On information and sufficiency'. The Annals of Mathematical Statistics, 1951: p. 79-86. [19] J. Leskovec, L. Backstrom, and J. Kleinberg, 'Meme-tracking and the dynamics of the news cycle', in Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2009, ACM: Paris, France. p. 497-506. [20] Y. Liu, 'Word of mouth for movies: Its dynamics and impact on box office revenue'. Journal of Marketing, 2006: p. 74-89. [21] R. Neelamegham and P. Chintagunta, 'A Bayesian model to forecast new product performance in domestic and international markets'. Marketing Science, 1999. 18(2): p. 115-136. [22] M.G. Rodriguez, J. Leskovec, B. Sch, #246, and lkopf, 'Structure and dynamics of information pathways in online media', in Proceedings of the Sixth ACM International Conference on Web Search and Data Mining. 2013, ACM: Rome, Italy. p. 23-32. [23] M.S. Sawhney and J. Eliashberg, 'A parsimonious model for forecasting gross box-office revenues of motion pictures'. Marketing Science, 1996. 15(2): p. 113-131. [24] S. Shugan and J. Swait, 'Enabling movie design and cumulative box office predictions using historical data and consumer intent-to-view'. University of Florida, working paper, 2000. [25] D.J. Watts and P.S. Dodds, 'Influentials, networks, and public opinion formation'. Journal of Consumer Research, 2007. 34(4): p. 441-458. [26] J. Yang and J. Leskovec, 'Modeling information diffusion in implicit networks', in Proceedings of the 2010 IEEE International Conference on Data Mining. 2010, IEEE Computer Society. p. 599-608. [27] W. Zhang and S. Skiena, 'Improving movie gross prediction through news analysis', in Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01. 2009, IEEE Computer Society. p. 301-304. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/57104 | - |
| dc.description.abstract | 隨著社群網路平台快速成長與成熟，越來越多人在社群網路上和大眾分享自己的意見及行為。Facebook的每日用戶數已高達八億，是近年來成長最迅速的社交網路之一。本研究旨在探討Facebook粉絲專頁之訊息傳播對於電影票房之影響力。首先，我們建立GIM模型，以估計使用者在粉絲頁上之影響力，並預測未來粉絲頁和粉絲之間的互動次數。接著，我們提出了一個線性迴歸模型，結合社群影響力及非社群的資訊，建立粉絲專頁和電影票房之間的關係。實驗結果顯示，社群影響力可明顯改善預測電影票房的準確度。 | zh_TW |
| dc.description.abstract | With the rapid growth and the maturity of online social networking applications, many people share their activities and opinions through social media. Facebook is one of the fastest growing social networks and has experienced a burst of popularity in recent years. In this study, we propose a framework to investigate the impact of social influence of a Facebook fan page on the movie box-office revenue. The proposed framework contains two phases. First, we develop the Global Influence Model to estimate the user influence and predict the engagements between the fan page and users. Next, we propose the Linear Box-Office Revenue Prediction Model to establish the relationship between Facebook fan pages and movie box-office revenues by utilizing the social influence and some statistics obtained from Facebook fan pages. The experiment results show that the accuracy of forecasting revenues for movies can be improved significantly by considering the social influence. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T06:35:02Z (GMT). No. of bitstreams: 1 ntu-103-R01725037-1.pdf: 766763 bytes, checksum: 2f83be645424f64303ceb4d8c52af091 (MD5) Previous issue date: 2014 | en |
| dc.description.tableofcontents | Table of Contents i
List of Figures ii List of Tables iii Chapter 1 Introduction 1 Chapter 2 Literature Survey 4 Chapter 3 Problem Definitions 6 Chapter 4 The Proposed Framework 7 4.1 Global Influence Model (GIM) 8 4.2 Linear Box-Office Prediction Model (LBRPM) 9 Chapter 5 Experiments 11 5.1 Settings 11 5.2 Results of Revenue Prediction 14 5.3 Parameters Analysis 17 5.3.1 Engagements at Time t or t+1 17 5.3.2 The Observation Time of the GIM Model 19 5.3.3 N in the GIM Model 19 5.4 Discussions 20 Chapter 6 Conclusions and Future Work 24 References 25 | |
| dc.language.iso | zh-TW | |
| dc.subject | 訊息傳播 | zh_TW |
| dc.subject | 社群網路 | zh_TW |
| dc.subject | 時間序列預測 | zh_TW |
| dc.subject | social network | en |
| dc.subject | information diffusion | en |
| dc.subject | time-series prediction | en |
| dc.title | Facebook粉絲頁之訊息傳播於電影票房之影響 | zh_TW |
| dc.title | Information Diffusion among Users on Facebook Fan Pages over Time: Its Impact on Box-Office Revenues for Movies | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 102-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.coadvisor | 葉彌妍(Mi-Yen Yeh) | |
| dc.contributor.oralexamcommittee | 陳建錦(Chien-Chin Chen) | |
| dc.subject.keyword | 社群網路,訊息傳播,時間序列預測, | zh_TW |
| dc.subject.keyword | social network,information diffusion,time-series prediction, | en |
| dc.relation.page | 27 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2014-08-04 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 資訊管理學研究所 | zh_TW |
| 顯示於系所單位： | 資訊管理學系 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-103-1.pdf 未授權公開取用 | 748.79 kB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。