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Sentiment Analysis with Instagram Data

Year 2020, Ejosat Special Issue 2020 (HORA), 360 - 364, 15.08.2020
https://doi.org/10.31590/ejosat.780129

Abstract

In this study, as a result of emoji classification, comparison of two smart phone brands was made. In the first part of the study, thanks to Selenium, the relevant instagram pages were reached and the comments of the first posts were put into practice. In this section, it is aimed to extract data without using additional libraries and user logins. For this purpose, proper waiting times are added for loading the page. In the second part of the study, the collected emojis were classified as positive, negative and neutral, and the results were presented in a pie chart.

References

  • Koçoğlu, S. (2018). Instagram Tarihi: Instagram Nedir? Nasıl Kullanılır? Ne İşe Yarar.
  • Şen E. (2017). Emojilerin Şaşırtan Hikayesi ve Teknik İşleyişi. https://emoji.com.tr/emojilerin-sasirtan-hikayesi/
  • Hutto, C. J., & 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.
  • Pandey, P. (2018). Simplifying Sentiment Analysis using VADER in Python (on Social Media Text). https://medium.com/analytics-vidhya/simplifying-social-media-sentiment-analysis-using-vader-in-python-f9e6ec6fc52f
  • Araque, O., Zhu, G., & Iglesias, C. A. (2019). A semantic similarity-based perspective of affect lexicons for sentiment analysis. Knowledge-Based Systems, 165, 346-359.
  • http://t-redactyl.io/blog/2017/04/using-vader-to-handle-sentiment-analysis-with-social-media-text.html
  • Rahul Vaish,2018, VADER and Sentiment Analysis — Python
  • https://medium.com/@rahulvaish/vader-and-sentiment-analysis-python-eae70ecef454
  • Urologin, S. (2018). Sentiment Analysis, Visualization and Classification of Summarized News Articles: A Novel Approach. International Journal of Advanced Computer Science and Applications, 9(8).
  • Poecze, F., Ebster, C., & Strauss, C. (2018). Social media metrics and sentiment analysis to evaluate the effectiveness of social media posts. Procedia computer science, 130, 660-666.

Instagram Verileri ile Duygu Analizi

Year 2020, Ejosat Special Issue 2020 (HORA), 360 - 364, 15.08.2020
https://doi.org/10.31590/ejosat.780129

Abstract

Bu çalışmada emoji sınıflandırılması sonucunda iki adet akıllı telefon markasının karşılaştırılması yapılmıştır. Çalışmanın birinci kısmında Selenium sayesinde ilgili instagram sayfalarına ulaşılarak ilk gönderilerin yorumları uygulamaya çekilmiştir. Bu kısımda ek kütüphane kullanmadan, kullanıcı girişi yapmadan verilerin çekilmesi hedeflenmektedir. Bu amaçla sayfanın yüklenmesini bekleyen uygun bekleme süreleri eklenmiştir. Çalışmanın ikinci kısmında ise çekilen emojiler başlangıçta ayarlandığı üzere pozitif, negatif ve nötr olarak sınıflandırılmış ve sonuç pasta grafiğinde oranlara dökülmüştür.

References

  • Koçoğlu, S. (2018). Instagram Tarihi: Instagram Nedir? Nasıl Kullanılır? Ne İşe Yarar.
  • Şen E. (2017). Emojilerin Şaşırtan Hikayesi ve Teknik İşleyişi. https://emoji.com.tr/emojilerin-sasirtan-hikayesi/
  • Hutto, C. J., & 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.
  • Pandey, P. (2018). Simplifying Sentiment Analysis using VADER in Python (on Social Media Text). https://medium.com/analytics-vidhya/simplifying-social-media-sentiment-analysis-using-vader-in-python-f9e6ec6fc52f
  • Araque, O., Zhu, G., & Iglesias, C. A. (2019). A semantic similarity-based perspective of affect lexicons for sentiment analysis. Knowledge-Based Systems, 165, 346-359.
  • http://t-redactyl.io/blog/2017/04/using-vader-to-handle-sentiment-analysis-with-social-media-text.html
  • Rahul Vaish,2018, VADER and Sentiment Analysis — Python
  • https://medium.com/@rahulvaish/vader-and-sentiment-analysis-python-eae70ecef454
  • Urologin, S. (2018). Sentiment Analysis, Visualization and Classification of Summarized News Articles: A Novel Approach. International Journal of Advanced Computer Science and Applications, 9(8).
  • Poecze, F., Ebster, C., & Strauss, C. (2018). Social media metrics and sentiment analysis to evaluate the effectiveness of social media posts. Procedia computer science, 130, 660-666.
There are 10 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

Pınar Kırcı

Elanur Gülbak This is me

Publication Date August 15, 2020
Published in Issue Year 2020 Ejosat Special Issue 2020 (HORA)

Cite

APA Kırcı, P., & Gülbak, E. (2020). Instagram Verileri ile Duygu Analizi. Avrupa Bilim Ve Teknoloji Dergisi360-364. https://doi.org/10.31590/ejosat.780129