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  1. NTU Theses and Dissertations Repository
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請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/61090
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dc.contributor.advisor曹承礎(Seng-Cho T. Chou)
dc.contributor.authorYi-Chun Linen
dc.contributor.author林怡君zh_TW
dc.date.accessioned2021-06-16T10:45:52Z-
dc.date.available2015-08-14
dc.date.copyright2013-08-14
dc.date.issued2013
dc.date.submitted2013-08-12
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Cha, M., Haddadi, H., Benevenuto, F., & Gummadi, K. P. (2010). Measuring user influence in Twitter: The million follower fallacy. Paper presented at the in ICWSM '10: Proceedings of international AAAI Conference on Weblogs and Social.
Cheng, A., Evans, M., & Koudas, N. (2009). Inside the Political Twittersphere Retrieved July 13, 2012, from http://www.sysomos.com/insidetwitter/politics/
Christie, M. J., & Venables, P. H. (1973). Mood Changes in Relation to Age, EPI Scores, Time and Day. British Journal of Social and Clinical Psychology, 12(1), 61-72. doi: 10.1111/j.2044-8260.1973.tb00846.x
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Go, A., Huang, L., & Bhayani, R. (2009). Twitter sentiment analysis. In F. P. f. C. N. f. S. a. T. S. N. L. P. Group (Ed.).
Hay, B. (2010). Twitter Twitter - but Who Is Listening?: A Review of the Current and Potential Use of Twittering as a Tourism Marketing Tool. Paper presented at the Council for Australian University Tourism and Hospitality Education (20th : 2010 : Hobart, Tas.), Hobart, Tas. http://search.informit.com.au/documentSummary;dn=815137574780835;res=IE LBUS
Jeon, J., & McSharry, P. (2012). The Power of Twitter on Predicting Box Office Revenues: Smith School of Enterprise and the Environment, University of Oxford.
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Longueville, B. D., Smith, R. S., & Luraschi, G. (2009). 'OMG, from here, I can see the flames!': a use case of mining location based social networks to acquire spatio-temporal data on forest fires. Paper presented at the Proceedings of the 2009 International Workshop on Location Based Social Networks, Seattle, Washington.
Mahmud, J., Nichols, J., & Drews, C. (2012). Where Is This Tweet From? Inferring Home Locations of Twitter Users. Paper presented at the ICWSM. http://dblp.uni-trier.de/db/conf/icwsm/icwsm2012.html#MahmudND12
McFarlane, J., Martin, C. L., & Williams, T. M. (1988). Mood Fluctuations. Psychology of Women Quarterly, 12(2), 201-223. doi: 10.1111/j.1471-6402.1988.tb00937.x
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Pak, A., & Paroubek, P. (2010b). Twitter based system: Using Twitter for disambiguating sentiment ambiguous adjectives. Paper presented at the Proceedings of the 5th International Workshop on Semantic Evaluation, Los Angeles, California.
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/61090-
dc.description.abstract趨勢分析一直是個熱門的研究議題,隨著社群網絡的蓬勃發展,社群網路的趨勢分析成為非常熱門的研究議題。本研究看中社群網絡的潛力,希望能透過社群網路的趨勢分析來了解使用者之情緒與購買意願的相關性。期待這樣的研究能帶給網路行銷嶄新的思維,使得社群網絡成為良好的銷售平台。
本研究選擇Twitter來做為趨勢分析的社群網路平台,透過Twitter所提供的應用程式介面(API, Application Programming Interface)來蒐集使用者每天發表的短文。針對這些短文,我們將對其進行情緒與購買意願的分析,最後透過統計方法來了解情緒與購買意願的關聯與時間相關性。
本研究探討情緒是否對購買意願造成影響,人們是否傾向於在情緒低落的時候購物?同時,我們常聽到的Monday blue是否真實存在?人們情緒的波動真的與星期有關嗎?
zh_TW
dc.description.abstractTrend analysis has been an important topic for data mining, while the prevailing of social networking, more and more trend analysis research focuses on social networking. Our research looks up on the potential of social networking, and is eager to find out the correlation between user emotion and buying intention through social network trend analysis. Hoping this kind of researches is able to provide new thoughts for internet marketing in the future, and making social networking becomes a good marketing platform.
In this research, we choose Twitter as the social networking site for trend analysis. Through Twitter provided API, we are able to collect users’ daily tweets. After preprocessing of those tweets, sentiment and buying intention of the tweets can be revealed. We’ll be able to use statistics analysis to verify the correlation between emotion and buying intention along with time series.
Our research focuses on whether user’s emotion affects user’s buying intention? Do people tend to shopping when they are down? Also, we often heard “Monday blue”, does Monday blue really exists? Is human’s emotion correlated with weekdays?
en
dc.description.provenanceMade available in DSpace on 2021-06-16T10:45:52Z (GMT). No. of bitstreams: 1
ntu-102-R00725034-1.pdf: 649319 bytes, checksum: 1f4835fd5a25cb4ce3af9808116a5ed1 (MD5)
Previous issue date: 2013
en
dc.description.tableofcontents致謝 i
中文摘要 ii
Abstract iii
Contents iv
List of Figures vi
List of Tables viii
Chapter 1 Introduction 1
1.1 Research Background and Motivation 1
1.2 Research Questions 2
Chapter 2 Literature Review 3
2.1 Social Network Analysis 3
2.1.1 Introduction of Social Network Analysis 3
2.1.2 Twitter 4
2.1.3 Trend Mining and Prediction on Social Network 4
2.2 Emotion and Its Cycle 6
2.2.1 Correlations between Emotion Cycle and Weekdays 6
2.2.2 The Blue Monday Phenomenon 6
2.3 Emotional Cycle and Intention of Purchase 7
2.3.1 Sentiment Analysis on Twitter 7
2.3.2 Marketing via Social Network 8
2.3.3 Emotion and Marketing 10
2.3.4 Correlate Emotional Cycle and Purchase Intention 10
Chapter 3 Research Approach 12
3.1 Data Collection 12
3.2 Data Preprocess 14
3.3 Data Analysis 16
Chapter 4 Data Analysis 19
4.1 Data Collected 19
4.2 Data Filtering 20
4.3 Correlation between Emotion and Buying Intention 22
Chapter 5 Discussion and Conclusion 25
5.1 Discussion 25
5.1.1 Research Finding 25
5.1.2 Research Limitations 26
5.1.3 Recommendations for Future Research 27
5.2 Conclusion 28
Appendix 29
REFERENCE 37
dc.language.isozh-TW
dc.subject網路行銷zh_TW
dc.subject社會網路分析zh_TW
dc.subject購買意願zh_TW
dc.subject情緒週期zh_TW
dc.subject銷售平台zh_TW
dc.subjectsocial network analysisen
dc.subjecte-marketingen
dc.subjectmarketing platformen
dc.subjectemotion cycleen
dc.subjectbuying intentionen
dc.title以Twitter來當作銷售平台:情緒週期與購買意願之相關性研究zh_TW
dc.titleUsing Twitter as a Marketing Platform: Correlating Emotional Cycle with Buying Intentionen
dc.typeThesis
dc.date.schoolyear101-2
dc.description.degree碩士
dc.contributor.oralexamcommittee陳文國(Wenkuo Chen),王貞雅(Grace Wang)
dc.subject.keyword社會網路分析,購買意願,情緒週期,銷售平台,網路行銷,zh_TW
dc.subject.keywordsocial network analysis,buying intention,emotion cycle,marketing platform,e-marketing,en
dc.relation.page39
dc.rights.note有償授權
dc.date.accepted2013-08-13
dc.contributor.author-college管理學院zh_TW
dc.contributor.author-dept資訊管理學研究所zh_TW
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