Tweet Sentiment Analysis for Cryptocurrencies

Emre Şaşmaz, F. Boray Tek

Araştırma sonucu: ???type-name???Konferans katkısıbilirkişi

21 Atıf (Scopus)

Özet

Many traders believe in and use Twitter tweets to guide their daily cryptocurrency trading. In this project, we investigated the feasibility of automated sentiment analysis for cryptocurrencies. For the study, we targeted one cryptocurrency (NEO) altcoin and collected related data. The data collection and cleaning were essential components of the study. First, the last five years of daily tweets with NEO hashtags were obtained from Twitter. The collected tweets were then filtered to contain or mention only NEO. We manually tagged a subset of the tweets with positive, negative, and neutral sentiment labels. We trained and tested a Random Forest classifier on the labeled data where the test set accuracy reached 77%. In the second phase of the study, we investigated whether the daily sentiment of the tweets was correlated with the NEO price. We found positive correlations between the number of tweets and the daily prices, and between the prices of different crypto coins. We share the data publicly.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıProceedings - 6th International Conference on Computer Science and Engineering, UBMK 2021
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
Sayfalar613-618
Sayfa sayısı6
ISBN (Elektronik)9781665429085
DOI'lar
Yayın durumuYayınlandı - 2021
Harici olarak yayınlandıEvet
Etkinlik6th International Conference on Computer Science and Engineering, UBMK 2021 - Ankara, Turkey
Süre: 15 Eyl 202117 Eyl 2021

Yayın serisi

AdıProceedings - 6th International Conference on Computer Science and Engineering, UBMK 2021

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???event.eventtypes.event.conference???6th International Conference on Computer Science and Engineering, UBMK 2021
Ülke/BölgeTurkey
ŞehirAnkara
Periyot15/09/2117/09/21

Bibliyografik not

Publisher Copyright:
© 2021 IEEE

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