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SOCIAL MEDIA INTERACTION OF FOREIGN USERS IN GETIR OF TURKEY'S SECOND UNICORN: TWITTER SENTIMENT ANALYSIS

Yıl 2022, Cilt: 20 Sayı: 4, 447 - 462, 31.12.2022
https://doi.org/10.11611/yead.1167146

Öz

Social media interactions, the digital form of classical word-of-mouth marketing (AAP), used to strengthen the business-brand image, have become one of the most critical evaluation criteria today. It is known how effective social media is in maximizing brand awareness and sales. For this purpose, the social media contents of the users abroad of Getir, Turkey's largest unicorn company, were analyzed. In this direction, the contents of the tweets posted in English from July 1, 2021, when Getir was launched to the European market in general, until July 1, 2022, were analyzed. Python programming language was used for data collection, and R language was used for data analysis. Social network analysis (SAA) of the most used words in the context of positive, negative, anger, anticipation, disgust, fear, joy, sadness, surprise, and trust of the emotional states of the tweets posted for Getir was performed. Social network analysis (SAA) was conducted in the context of positive, negative, anger, anticipation, disgust, fear, joy, sadness, surprise, and trust of the most used words in the emotional states of tweets for Getir. As a result of the analysis, it was determined that the positive emotions of the users towards Getir were higher than the negative emotions. It has been determined that the company's development performance and social media analysis results are in parallel.

Kaynakça

  • Antonakaki, D., Fragopoulou, P., and Ioannidis, S. (2021). A survey of Twitter research: Data model, graph structure, sentiment analysis and attacks. Expert Systems with Applications, 164, 114006.
  • Arifianto, C., and Veritia, V. (2022). Social Network Analysis: A Competition in Indonesia’s Fastest Growing Fintech. Jurnal Manajemen dan Kewirausahaan, 24(1), 73-80.
  • Beck, M. 2020, How to Scrape Tweets With snscrape. Date of Access:05.05.2022. Url:https://betterprogramming.pub/how-to-scrape-tweets-with-snscrape-90124ed006af
  • Chung, W. Y., Jo, Y., and Lee, D. (2021). Where should ICT startup companies be established? Efficiency comparison between cluster types. Telematics and Informatics, 56, 101482.
  • Chursook, A., Dawod, A. Y., Chanaim, S., Naktnasukanjn, N., and Chakpitak, N. (2022). Twitter Sentiment Analysis and Expert Ratings of Initial Coin Offering Fundraising: Evidence from Australia and Singapore Markets.
  • Fijačko, N., Creber, R. M., Štiglic, G., Kocbek, P., Skok, P., and Greif, R. (2021). Public sentiment analysis of Twitter reaction on sudden cardiac arrest at EURO 2020. Resuscitation, 167, 427-429.
  • Getir, (2022). Our Story, Date of Access: 01.08.2022 Url:https://career.getir.com/
  • Hassan, M. K., Hudaefi, F. A., and Caraka, R. E. (2021). Mining netizen’s opinion on cryptocurrency: Sentiment analysis of Twitter data. Studies in Economics and Finance.
  • Indrawati and Putri, N. W. N. S. T. (2021, October). User Generated Content on Twitter to Identify Market Insights: a Case study on Zenius. In 2021 International Conference Advancement in Data Science, E-learning and Information Systems (ICADEIS) (pp. 1-6). IEEE.
  • Kafeza, E., Makris, C., Rompolas, G., and Al-Obeidat, F. (2021). Behavioral and migration analysis of the dynamic customer relationships on Twitter. Information Systems Frontiers, 23(5), 1303-1316.
  • Kaur, M., Verma, R., and Otoo, F. N. K. (2021). Emotions in leader’s crisis communication: Twitter sentiment analysis during COVID-19 outbreak. Journal of Human Behavior in the Social Environment, 31(1-4), 362-372.
  • Korkmaz, A. (2021). Dijital Çağda Bilgi Yönetimi Sistemleri: Sosyal Medya. Talan T., Aktürk C. (Ed) Dijital Dönüşüm ve Bilişim Sistemleri, (s. 19-39). Efe Akademi Yayınevi
  • Liu, B. (2020). Sentiment analysis: Mining opinions, sentiments, and emotions. Cambridge university press.
  • Michaelidou, N., Siamagka, N. T., and Christodoulides, G. (2011). Usage, barriers, and measurement of social media marketing: An exploratory investigation of small and medium B2B brands. Industrial marketing management, 40(7), 1153-1159.
  • Mohammad, S. M., and Turney, P. D. (2013). NRC emotion lexicon (p. 234). National Research Council of Canada. https://doi.org/10.4224/21270984
  • Nistor, S. C., Moca, M., Moldovan, D., Oprean, D. B., and Nistor, R. L. (2021). Building a Twitter sentiment analysis system with recurrent neural networks. Sensors, 21(7), 2266.
  • Raza, M. R., Hussain, W., Tanyıldızı, E., and Varol, A. (2021, June). Sentiment analysis using deep learning in cloud. In 2021 9th International Symposium on Digital Forensics and Security (ISDFS) (pp. 1-5). IEEE.
  • Rodrigues, C. D., and de Noronha, M. E. S. (2021). What companies can learn from unicorn startups to overcome the COVID-19 crisis. Innovation & Management Review.
  • Saura, J. R., Palos-Sanchez, P., and Grilo, A. (2019). Detecting indicators for startup business success: Sentiment analysis using text data mining. Sustainability, 11(3), 917.
  • Singhal, J., Rane, C., Wadalkar, Y., Joshi, M., and Deshpande, A. (2022, January). Data-Driven Analysis for Startup Investments for Venture Capitalists. In 2022 International Conference for Advancement in Technology (ICONAT) (pp. 1-6). IEEE.
  • Thakkar, H., and Patel, D. (2015). Approaches for sentiment analysis on Twitter: A state-of-art study. arXiv preprint arXiv:1512.01043.
  • Tian, X., He, W., and Wang, F. K. (2021). Applying sentiment analytics to examine social media crises: a case study of United Airlines’ crisis in 2017. Data Technologies and Applications.
  • Trivedi, S. K., and Singh, A. (2021). Twitter sentiment analysis of app-based online food delivery companies. Global Knowledge, Memory, and Communication.
  • Voicu-Dorobanţu, R., Jinaru, A., and Caragea, A. (2014). The Collaborative Poles Network and The Development Of An Efficient Entrepreneurial Ecosystem. Sea: Practical Application of Science, 2(3).
  • WeAreSocial, (2022). Digital 2022: Another Year of Bumper Growth. Url: https://wearesocial.com/uk/blog/2022/01/digital-2022-another-year-of-bumper-growth-2/ Date of Access:08.05.2022
Yıl 2022, Cilt: 20 Sayı: 4, 447 - 462, 31.12.2022
https://doi.org/10.11611/yead.1167146

Öz

Kaynakça

  • Antonakaki, D., Fragopoulou, P., and Ioannidis, S. (2021). A survey of Twitter research: Data model, graph structure, sentiment analysis and attacks. Expert Systems with Applications, 164, 114006.
  • Arifianto, C., and Veritia, V. (2022). Social Network Analysis: A Competition in Indonesia’s Fastest Growing Fintech. Jurnal Manajemen dan Kewirausahaan, 24(1), 73-80.
  • Beck, M. 2020, How to Scrape Tweets With snscrape. Date of Access:05.05.2022. Url:https://betterprogramming.pub/how-to-scrape-tweets-with-snscrape-90124ed006af
  • Chung, W. Y., Jo, Y., and Lee, D. (2021). Where should ICT startup companies be established? Efficiency comparison between cluster types. Telematics and Informatics, 56, 101482.
  • Chursook, A., Dawod, A. Y., Chanaim, S., Naktnasukanjn, N., and Chakpitak, N. (2022). Twitter Sentiment Analysis and Expert Ratings of Initial Coin Offering Fundraising: Evidence from Australia and Singapore Markets.
  • Fijačko, N., Creber, R. M., Štiglic, G., Kocbek, P., Skok, P., and Greif, R. (2021). Public sentiment analysis of Twitter reaction on sudden cardiac arrest at EURO 2020. Resuscitation, 167, 427-429.
  • Getir, (2022). Our Story, Date of Access: 01.08.2022 Url:https://career.getir.com/
  • Hassan, M. K., Hudaefi, F. A., and Caraka, R. E. (2021). Mining netizen’s opinion on cryptocurrency: Sentiment analysis of Twitter data. Studies in Economics and Finance.
  • Indrawati and Putri, N. W. N. S. T. (2021, October). User Generated Content on Twitter to Identify Market Insights: a Case study on Zenius. In 2021 International Conference Advancement in Data Science, E-learning and Information Systems (ICADEIS) (pp. 1-6). IEEE.
  • Kafeza, E., Makris, C., Rompolas, G., and Al-Obeidat, F. (2021). Behavioral and migration analysis of the dynamic customer relationships on Twitter. Information Systems Frontiers, 23(5), 1303-1316.
  • Kaur, M., Verma, R., and Otoo, F. N. K. (2021). Emotions in leader’s crisis communication: Twitter sentiment analysis during COVID-19 outbreak. Journal of Human Behavior in the Social Environment, 31(1-4), 362-372.
  • Korkmaz, A. (2021). Dijital Çağda Bilgi Yönetimi Sistemleri: Sosyal Medya. Talan T., Aktürk C. (Ed) Dijital Dönüşüm ve Bilişim Sistemleri, (s. 19-39). Efe Akademi Yayınevi
  • Liu, B. (2020). Sentiment analysis: Mining opinions, sentiments, and emotions. Cambridge university press.
  • Michaelidou, N., Siamagka, N. T., and Christodoulides, G. (2011). Usage, barriers, and measurement of social media marketing: An exploratory investigation of small and medium B2B brands. Industrial marketing management, 40(7), 1153-1159.
  • Mohammad, S. M., and Turney, P. D. (2013). NRC emotion lexicon (p. 234). National Research Council of Canada. https://doi.org/10.4224/21270984
  • Nistor, S. C., Moca, M., Moldovan, D., Oprean, D. B., and Nistor, R. L. (2021). Building a Twitter sentiment analysis system with recurrent neural networks. Sensors, 21(7), 2266.
  • Raza, M. R., Hussain, W., Tanyıldızı, E., and Varol, A. (2021, June). Sentiment analysis using deep learning in cloud. In 2021 9th International Symposium on Digital Forensics and Security (ISDFS) (pp. 1-5). IEEE.
  • Rodrigues, C. D., and de Noronha, M. E. S. (2021). What companies can learn from unicorn startups to overcome the COVID-19 crisis. Innovation & Management Review.
  • Saura, J. R., Palos-Sanchez, P., and Grilo, A. (2019). Detecting indicators for startup business success: Sentiment analysis using text data mining. Sustainability, 11(3), 917.
  • Singhal, J., Rane, C., Wadalkar, Y., Joshi, M., and Deshpande, A. (2022, January). Data-Driven Analysis for Startup Investments for Venture Capitalists. In 2022 International Conference for Advancement in Technology (ICONAT) (pp. 1-6). IEEE.
  • Thakkar, H., and Patel, D. (2015). Approaches for sentiment analysis on Twitter: A state-of-art study. arXiv preprint arXiv:1512.01043.
  • Tian, X., He, W., and Wang, F. K. (2021). Applying sentiment analytics to examine social media crises: a case study of United Airlines’ crisis in 2017. Data Technologies and Applications.
  • Trivedi, S. K., and Singh, A. (2021). Twitter sentiment analysis of app-based online food delivery companies. Global Knowledge, Memory, and Communication.
  • Voicu-Dorobanţu, R., Jinaru, A., and Caragea, A. (2014). The Collaborative Poles Network and The Development Of An Efficient Entrepreneurial Ecosystem. Sea: Practical Application of Science, 2(3).
  • WeAreSocial, (2022). Digital 2022: Another Year of Bumper Growth. Url: https://wearesocial.com/uk/blog/2022/01/digital-2022-another-year-of-bumper-growth-2/ Date of Access:08.05.2022
Toplam 25 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Finans
Bölüm Makaleler
Yazarlar

Adem Korkmaz 0000-0002-7530-7715

Yayımlanma Tarihi 31 Aralık 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 20 Sayı: 4

Kaynak Göster

APA Korkmaz, A. (2022). SOCIAL MEDIA INTERACTION OF FOREIGN USERS IN GETIR OF TURKEY’S SECOND UNICORN: TWITTER SENTIMENT ANALYSIS. Yönetim Ve Ekonomi Araştırmaları Dergisi, 20(4), 447-462. https://doi.org/10.11611/yead.1167146
AMA Korkmaz A. SOCIAL MEDIA INTERACTION OF FOREIGN USERS IN GETIR OF TURKEY’S SECOND UNICORN: TWITTER SENTIMENT ANALYSIS. Yönetim ve Ekonomi Araştırmaları Dergisi. Aralık 2022;20(4):447-462. doi:10.11611/yead.1167146
Chicago Korkmaz, Adem. “SOCIAL MEDIA INTERACTION OF FOREIGN USERS IN GETIR OF TURKEY’S SECOND UNICORN: TWITTER SENTIMENT ANALYSIS”. Yönetim Ve Ekonomi Araştırmaları Dergisi 20, sy. 4 (Aralık 2022): 447-62. https://doi.org/10.11611/yead.1167146.
EndNote Korkmaz A (01 Aralık 2022) SOCIAL MEDIA INTERACTION OF FOREIGN USERS IN GETIR OF TURKEY’S SECOND UNICORN: TWITTER SENTIMENT ANALYSIS. Yönetim ve Ekonomi Araştırmaları Dergisi 20 4 447–462.
IEEE A. Korkmaz, “SOCIAL MEDIA INTERACTION OF FOREIGN USERS IN GETIR OF TURKEY’S SECOND UNICORN: TWITTER SENTIMENT ANALYSIS”, Yönetim ve Ekonomi Araştırmaları Dergisi, c. 20, sy. 4, ss. 447–462, 2022, doi: 10.11611/yead.1167146.
ISNAD Korkmaz, Adem. “SOCIAL MEDIA INTERACTION OF FOREIGN USERS IN GETIR OF TURKEY’S SECOND UNICORN: TWITTER SENTIMENT ANALYSIS”. Yönetim ve Ekonomi Araştırmaları Dergisi 20/4 (Aralık 2022), 447-462. https://doi.org/10.11611/yead.1167146.
JAMA Korkmaz A. SOCIAL MEDIA INTERACTION OF FOREIGN USERS IN GETIR OF TURKEY’S SECOND UNICORN: TWITTER SENTIMENT ANALYSIS. Yönetim ve Ekonomi Araştırmaları Dergisi. 2022;20:447–462.
MLA Korkmaz, Adem. “SOCIAL MEDIA INTERACTION OF FOREIGN USERS IN GETIR OF TURKEY’S SECOND UNICORN: TWITTER SENTIMENT ANALYSIS”. Yönetim Ve Ekonomi Araştırmaları Dergisi, c. 20, sy. 4, 2022, ss. 447-62, doi:10.11611/yead.1167146.
Vancouver Korkmaz A. SOCIAL MEDIA INTERACTION OF FOREIGN USERS IN GETIR OF TURKEY’S SECOND UNICORN: TWITTER SENTIMENT ANALYSIS. Yönetim ve Ekonomi Araştırmaları Dergisi. 2022;20(4):447-62.