Journals / Yönetim ve Ekonomi Araştırmaları Dergisi / 2022 / Cilt: 20 - Sayı: 4

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

Pages
447–462
Publication Date
2022-12-31
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

It has been determined that the company's development performance and social media analysis results are in parallel.

📌 3 Key Takeaways

🎯
Objective & Hypothesis: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.
📊
Key Findings & Data: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.
💡
Conclusion & Impact:It has been determined that the company's development performance and social media analysis results are in parallel.
🔬Design:Research Article
📍Scope:2021 Verileri
⚙️Variables:Getir Unicorn · Twitter Sentiment Analysis · Social Media Analysis

Abstract

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.

🔖

Cite This Article

KORKMAZ, A. (2022). SOCIAL MEDIA INTERACTION OF FOREIGN USERS IN GETIR OF TURKEY'S SECOND UNICORN: TWITTER SENTIMENT ANALYSIS. Yönetim ve Ekonomi Araştırmaları Dergisi, Cilt: 20 - Sayı: 4, 447–462. https://ajindex.com/articles/889872

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (9)

  1. 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.
  2. 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
  3. 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).
  4. Our Story, Date of Access: 01.08.2022 Url:https://career.getir.com/
  5. 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).
  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.
  7. 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.
  8. Korkmaz, A. (2021). Dijital Çağda Bilgi Yönetimi Sistemleri: Sosyal Medya. Talan T., Aktürk C. (Ed) Dijital Dönüşüm ve Bilişim Sistemleri, (s. 19-39).
  9. 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 med