Research Article
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Ranking of Black Friday Hashtags with Tweet Statics and Sentiment Analysis

Year 2020, Volume: 23 Issue: 1, 131 - 140, 30.04.2020
https://doi.org/10.29249/selcuksbmyd.638064

Abstract

Social media is a very popular communication tool for sharing people's activities, ideas and feelings with others. Twitter is one of the most popular of these social media platforms. On Twitter many tweets are made about shopping campaigns at special times such as Mother's Day, Valentine's Day, and Black Friday week. Firms all over the world as well as firms in Turkey, in this special shopping periods are trying to attract customers' attention with the hashtags they create on social media.
In this study, alternative Black Friday hashtags are discussed. In 2018, tweets containing these hashtags were reviewed over a three-week period, including the week before and after the Black Friday week. The emotions contained in the tweets were determined by Sentiment Analysis. The total number of tweets, number of retweets, number of favorites and user information were used to ranking hashtags. For this purpose, hashtags are ranked in three different dimensions as numerical data, tweet values and tweet emotions. With this ranking, it is aimed to be a guide to the hashtag preference of brands.

References

  • Abbasi, A., Chen, H. ve Salem, A. (2008). Sentiment analysis in multiple languages: Feature selection for opinion classification in web forums. ACM Transactions on Information Systems (TOIS), 26(3), 12. 1-34.
  • Akgül, D. ve Varinli, İ. (2017). Hedonik (Hazcı) Tüketimin Özel Günlerdeki Alışveriş Kültürü Üzerindeki Etkisi ve Ülkelerarası Karşılaştırmalı Bir Araştırma. International Journal of Social Inquiry, 10(2).
  • Balahur, A., Steinberger, R., Kabadjov, M., Zavarella, V., Van Der Goot, E., Halkia, M., ... ve Belyaeva, J. (2013). Sentiment analysis in the news. arXiv preprint arXiv:1309.6202. 2216-2220.
  • Boyd Thomas, J. ve Peters, C. (2011). An exploratory investigation of Black Friday consumption rituals. International Journal of Retail & Distribution Management, 39(7), 522-537.
  • Cambria, E., Das, D., Bandyopadhyay, S. ve Feraco, A. (Eds.). (2017). A Practical Guide to Sentiment Analysis (Vol. 5). London: Springer.Dilek, Ö. (2018). Özel Günler İçin Yapılan Harcamaların Tüketici Bütçesindeki Yeri: Rize Örneği. ICPESS 2018 PROCEEDINGS Volume 2: Ecomonic Studies, 170-179.
  • Fang, X. ve Zhan, J. (2015). Sentiment analysis using product review data. Journal of Big Data, 2(1), 5, 1-14.
  • Güngör, Z., Serhadlıoğlu, G. ve Kesen, S. E. (2009). A fuzzy AHP approach to personnel selection problem. Applied Soft Computing, 9(2), 641-646.
  • Hutto, C. J. ve Gilbert, E. (2014, May). Vader: A parsimonious rule-based model for sentiment analysis of social media text. In Eighth international AAAI conference on weblogs and social media, 216-225
  • Lennon, S. J., Johnson, K. K. ve Lee, J. (2011). A perfect storm for consumer misbehavior: Shopping on Black Friday. Clothing and Textiles Research Journal, 29(2), 119-134.
  • Liu, B. (2012). Sentiment analysis and opinion mining. Synthesis lectures on human language technologies, 5(1), 1-167.
  • Mohammad, S. M., Kiritchenko, S. ve Zhu, X. (2013). NRC-Canada: Building the state-of-the-art in sentiment analysis of tweets. arXiv preprint arXiv:1308.6242. 1-7.
  • Mullen, T. ve Collier, N. (2004). Sentiment analysis using support vector machines with diverse information sources. In Proceedings of the 2004 conference on empirical methods in natural language processing, 412-418.
  • Ortigosa, A., Martín, J. M. ve Carro, R. M. (2014). Sentiment analysis in Facebook and its application to e-learning. Computers in human behavior, 31, 527-541.
  • Razis, G. ve Anagnostopoulos, I. (2014, September). InfluenceTracker: Rating the impact of a Twitter account. In IFIP International Conference on Artificial Intelligence Applications and Innovations (pp. 184-195). Springer, Berlin, Heidelberg.
  • Rosenthal, S., Farra, N. ve Nakov, P. (2017, August). SemEval-2017 task 4: Sentiment analysis in Twitter. In Proceedings of the 11th international workshop on semantic evaluation (SemEval-2017) (pp. 502-518).
  • Saura, J. R., Reyes-Menendez, A. ve Palos-Sanchez, P. (2019). Are Black Friday Deals Worth It? Mining Twitter Users’ Sentiment and Behavior Response. Journal of Open Innovation: Technology, Market, and Complexity, 5(3), 58, 1-13.
  • Smith, O. ve Raymen, T. (2017). Shopping with violence: Black Friday sales in the British context. Journal of Consumer Culture, 17(3), 677-694.
  • Tan, C., Lee, L., Tang, J., Jiang, L., Zhou, M. ve Li, P. (2011, August). User-level sentiment analysis incorporating social networks. In Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 1397-1405). ACM.
  • url1: https://wise.tv/videolar/etiyanin-yeni-urunu-cognitus-dogal-dil-isleme-alaninda-ne-seviyede.html, son erişim tarihi: 20.10.2019
  • url 2: https://cognitus.ai/wp-content/uploads/2019/05/Duygu-Analizi-Klavuzu.pdf, son erişim tarihi: 20.10.2019
  • Wang, X., Wei, F., Liu, X., Zhou, M. ve Zhang, M. (2011, October). Topic sentiment analysis in twitter: a graph-based hashtag sentiment classification approach. In Proceedings of the 20th ACM international conference on Information and knowledge management (pp. 1031-1040). ACM.
  • Wilson, T., Wiebe, J. ve Hoffmann, P. (2005, October). Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis. In Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing (pp. 347-354). Association for Computational Linguistics.

Kara Cuma Etiketlerinin Tweet İstatistikleri ve Duygu Analizi ile Sıralanması

Year 2020, Volume: 23 Issue: 1, 131 - 140, 30.04.2020
https://doi.org/10.29249/selcuksbmyd.638064

Abstract

Sosyal medya, insanların faaliyetlerini, fikirlerini ve duygularını başkalarıyla paylaşmak için çok popüler bir iletişim aracıdır. Twitter, bu sosyal medya platformlarının en popülerlerinden birisidir. Twitter’da alışverişin yoğun olduğu Anneler günü, Sevgililer günü, Kara Cuma haftası gibi özel zamanlarda alışveriş kampanyaları hakkında birçok tweet oluşturulmaktadır. Tüm dünyada olduğu gibi Türkiye'de de firmalar, bu özel alışveriş zamanlarında sosyal medyada oluşturdukları etiketler ile müşterilerin dikkatini çekmeye çalışmaktadırlar.
Bu çalışmada, birbirine alternatif Kara Cuma etiketleri ele alınmıştır. 2018 yılında Kara Cuma haftasından öncesi Kara Cuma haftası ve sonraki hafta olmak üzere 3 haftalık dönemde bu alternatif etiketleri içeren tweetler değerlendirilmiştir. Tweetlerin içerdiği duygular, duygu analizi ile belirlenmiştir. Etiketleri sıralamak için toplam tweet sayısı, retweet sayısı, beğeni sayısı ve kullanıcı bilgileri kullanılmıştır. Etiketler sayısal veriler, tweet değerleri, tweetlerin duygu değerleri olmak üzere üç farklı boyutta sıralanmıştır. Bu sıralama ile markaların etiket tercihine bir rehber olunması amaçlanmıştır.

References

  • Abbasi, A., Chen, H. ve Salem, A. (2008). Sentiment analysis in multiple languages: Feature selection for opinion classification in web forums. ACM Transactions on Information Systems (TOIS), 26(3), 12. 1-34.
  • Akgül, D. ve Varinli, İ. (2017). Hedonik (Hazcı) Tüketimin Özel Günlerdeki Alışveriş Kültürü Üzerindeki Etkisi ve Ülkelerarası Karşılaştırmalı Bir Araştırma. International Journal of Social Inquiry, 10(2).
  • Balahur, A., Steinberger, R., Kabadjov, M., Zavarella, V., Van Der Goot, E., Halkia, M., ... ve Belyaeva, J. (2013). Sentiment analysis in the news. arXiv preprint arXiv:1309.6202. 2216-2220.
  • Boyd Thomas, J. ve Peters, C. (2011). An exploratory investigation of Black Friday consumption rituals. International Journal of Retail & Distribution Management, 39(7), 522-537.
  • Cambria, E., Das, D., Bandyopadhyay, S. ve Feraco, A. (Eds.). (2017). A Practical Guide to Sentiment Analysis (Vol. 5). London: Springer.Dilek, Ö. (2018). Özel Günler İçin Yapılan Harcamaların Tüketici Bütçesindeki Yeri: Rize Örneği. ICPESS 2018 PROCEEDINGS Volume 2: Ecomonic Studies, 170-179.
  • Fang, X. ve Zhan, J. (2015). Sentiment analysis using product review data. Journal of Big Data, 2(1), 5, 1-14.
  • Güngör, Z., Serhadlıoğlu, G. ve Kesen, S. E. (2009). A fuzzy AHP approach to personnel selection problem. Applied Soft Computing, 9(2), 641-646.
  • Hutto, C. J. ve Gilbert, E. (2014, May). Vader: A parsimonious rule-based model for sentiment analysis of social media text. In Eighth international AAAI conference on weblogs and social media, 216-225
  • Lennon, S. J., Johnson, K. K. ve Lee, J. (2011). A perfect storm for consumer misbehavior: Shopping on Black Friday. Clothing and Textiles Research Journal, 29(2), 119-134.
  • Liu, B. (2012). Sentiment analysis and opinion mining. Synthesis lectures on human language technologies, 5(1), 1-167.
  • Mohammad, S. M., Kiritchenko, S. ve Zhu, X. (2013). NRC-Canada: Building the state-of-the-art in sentiment analysis of tweets. arXiv preprint arXiv:1308.6242. 1-7.
  • Mullen, T. ve Collier, N. (2004). Sentiment analysis using support vector machines with diverse information sources. In Proceedings of the 2004 conference on empirical methods in natural language processing, 412-418.
  • Ortigosa, A., Martín, J. M. ve Carro, R. M. (2014). Sentiment analysis in Facebook and its application to e-learning. Computers in human behavior, 31, 527-541.
  • Razis, G. ve Anagnostopoulos, I. (2014, September). InfluenceTracker: Rating the impact of a Twitter account. In IFIP International Conference on Artificial Intelligence Applications and Innovations (pp. 184-195). Springer, Berlin, Heidelberg.
  • Rosenthal, S., Farra, N. ve Nakov, P. (2017, August). SemEval-2017 task 4: Sentiment analysis in Twitter. In Proceedings of the 11th international workshop on semantic evaluation (SemEval-2017) (pp. 502-518).
  • Saura, J. R., Reyes-Menendez, A. ve Palos-Sanchez, P. (2019). Are Black Friday Deals Worth It? Mining Twitter Users’ Sentiment and Behavior Response. Journal of Open Innovation: Technology, Market, and Complexity, 5(3), 58, 1-13.
  • Smith, O. ve Raymen, T. (2017). Shopping with violence: Black Friday sales in the British context. Journal of Consumer Culture, 17(3), 677-694.
  • Tan, C., Lee, L., Tang, J., Jiang, L., Zhou, M. ve Li, P. (2011, August). User-level sentiment analysis incorporating social networks. In Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 1397-1405). ACM.
  • url1: https://wise.tv/videolar/etiyanin-yeni-urunu-cognitus-dogal-dil-isleme-alaninda-ne-seviyede.html, son erişim tarihi: 20.10.2019
  • url 2: https://cognitus.ai/wp-content/uploads/2019/05/Duygu-Analizi-Klavuzu.pdf, son erişim tarihi: 20.10.2019
  • Wang, X., Wei, F., Liu, X., Zhou, M. ve Zhang, M. (2011, October). Topic sentiment analysis in twitter: a graph-based hashtag sentiment classification approach. In Proceedings of the 20th ACM international conference on Information and knowledge management (pp. 1031-1040). ACM.
  • Wilson, T., Wiebe, J. ve Hoffmann, P. (2005, October). Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis. In Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing (pp. 347-354). Association for Computational Linguistics.
There are 22 citations in total.

Details

Primary Language Turkish
Journal Section Original Research Articles
Authors

Günay Kılıç 0000-0003-2236-7535

İbrahim Budak 0000-0001-7762-6114

Bedia Sündüz Kılıç This is me 0000-0003-3384-2725

Publication Date April 30, 2020
Submission Date October 25, 2019
Published in Issue Year 2020 Volume: 23 Issue: 1

Cite

APA Kılıç, G., Budak, İ., & Kılıç, B. S. (2020). Kara Cuma Etiketlerinin Tweet İstatistikleri ve Duygu Analizi ile Sıralanması. Selçuk Üniversitesi Sosyal Bilimler Meslek Yüksekokulu Dergisi, 23(1), 131-140. https://doi.org/10.29249/selcuksbmyd.638064

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