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Journals / Muş Alparslan Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi / 2021 / Cilt: 2 - Sayı: 2

Complexity Matrices in Twitter Sentiment Analysis of Thoughts on Mobile Games Using Machine Learning Algorithms

Erol KINA
Recep ÖZDAĞ
Pages
91–100
Publication Date
2021-12-29
DOI
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AI Summary & Key Takeaways

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

As a result of the analysis, it was found that multilayer artificial neural networks gave better results than the other methods on both training and test data.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In modern times, people have started sharing their opinions, thoughts and feelings with other people through social media.
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Key Findings & Data:Tweets that people write and share in 280 characters are used for research and analysis.
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Conclusion & Impact:As a result of the analysis, it was found that multilayer artificial neural networks gave better results than the other methods on both training and test data.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Mobil Oyunlar · Duygu analizi · Twitter

Abstract

In modern times, people have started sharing their opinions, thoughts and feelings with other people through social media. The growing number of social media users and their share in it has naturally drawn the attention of researchers to this field. Twitter is one of the leading data sources in this field. Since Twitter has millions of users from different cultures and classes, it is possible to collect comments in different languages and content. Tweets that people write and share in 280 characters are used for research and analysis. Considering the fact that not all tweets can be read by people, in this study, sentiment analysis was performed using naive bayes (NB) classification algorithm and multilayer artificial neural networks (ML-ANN) based on the content of comments on mobile games. As a result of the analysis, it was found that multilayer artificial neural networks gave better results than the other methods on both training and test data.

Özet

Günümüzde insanlar sosyal medya aracılığıyla fikir, düşünce ve duygularını diğer insanlarla paylaşmaya başladılar. Artan sosyal medya kullanıcıları ve paylaşımları, doğal olarak araştırmacıların dikkatini bu alana çekmiştir. Twitter bu alanda önde gelen veri kaynaklarından biridir. Twitter'ın farklı kültür ve sınıflardan milyonlarca kullanıcısı olduğu için farklı dillerde ve içeriklerde yorum toplamak mümkündür. İnsanların 280 karakterde yazıp paylaştığı tweetler araştırma ve analiz için kullanılmaktadır. Tüm tweetlerin insanlar tarafından okunamayacağı gerçeğinden hareketle bu çalışmada, mobil oyunlara yapılan yorumların içeriğine dayalı olarak naive bayes (NB) sınıflandırma algoritması ve çok katmanlı yapay sinir ağları (ML-ANN) kullanılarak duygu analizi yapılmıştır. Analiz sonucunda çok katmanlı yapay sinir ağlarının hem eğitim hem de test verileri üzerinde diğer yöntemlere göre daha iyi sonuçlar verdiği tespit edilmiştir.

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Cite This Article

KINA, E., ÖZDAĞ, R. (2021). Complexity Matrices in Twitter Sentiment Analysis of Thoughts on Mobile Games Using Machine Learning Algorithms. Muş Alparslan Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, Cilt: 2 - Sayı: 2, 91–100. https://ajindex.com/articles/854495

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