Research Article

STOCK SENTIMENT ANALYSIS FROM NEWS HEADLINES BY USING ENSEMBLE BOOSTING ALGORITHMS

Volume: 27 Number: 1 February 26, 2026
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STOCK SENTIMENT ANALYSIS FROM NEWS HEADLINES BY USING ENSEMBLE BOOSTING ALGORITHMS

Abstract

Stock sentiment analysis using machine learning techniques is an active area of research and development. Through these techniques, it is possible to analyze whether news headlines are likely to have a positive or negative sentiment, which is considered a potential factor influencing stock price movements. The analysis in this study is based on factors such as company-related news headlines and their publication dates. This study aims to introduce a stock sentiment analysis methodology based on Ensemble Boosting Algorithms. The dataset used consists of 3,897 unique news headlines from various companies. In addition to Ensemble Boosting Algorithms, widely used classification algorithms were also trained and compared. The results demonstrate that the proposed models achieved successful performance in sentiment classification.

Keywords

References

  1. Ali, S., & Yilmaz, A. (2021). Ensemble Learning for Enhanced Stock Sentiment Analysis Using Social Media and News Data. Journal of Financial Analytics, 17(3), 112–130.
  2. Atan, S., & Cinar, Y. (2019). Examining The Relationship Between Financial News and Market Value in Borsa Istanbul Using Text Mining and Sentiment Analysis. (Borsa Istanbul’da Finansal Haberler ile Piyasa Degeri İliskisinin Metin Madenciligi ve Duygu (Sentiment) Analizi ile İncelenmesi). Ankara University, The Faculty of Political Sciences Journal, 74 (1), pp. 1-34.
  3. Bacanin, N., Zivkovic, M., Stoean, C., Antonijevic, M., Janicijevic, S., Sarac, M., & Strumberger, I. (2022). Application of Natural Language Processing and Machine Learning Boosted with Swarm Intelligence for Spam E-mail Filtering. Mathematics, 10 (22), pp. 4173. https://doi.org/10.3390/math10224173
  4. Bentéjac, C., Csörgő, A., & Martínez-Muñoz, G. (2021). A comparative Analysis of Gradient Boosting Algorithms. Artificial Intelligence Review, 54, pp. 1937-1967. https://doi.org/10.1007/s10462-020-09896-5
  5. Bollen, J., Mao, H., & Zeng, X. (2011). Twitter Mood Predicts the Stock Market. Journal of Computational Science, 2 (1), pp. 1-8. https://doi.org/10.1016/j.jocs.2010.12.007
  6. Brown, T., & Nguyen, P. (2022). Portfolio Optimization Using Ensemble Learning Approaches. International Journal of Investment Science, 9(3), 230–245.
  7. Chen, S., Webb, G. I., Liu, L., & Ma, X. (2020). A novel selective naïve Bayes algorithm. Knowledge-Based Systems, 192, 105361. https://doi.org/10.1016/j.knosys.2019.105361
  8. Demajo, Lara. (2020). Explainable AI For Interpretable Credit Scoring. Thesis M.Sc. University of Malta.

Details

Primary Language

English

Subjects

Finance

Journal Section

Research Article

Publication Date

February 26, 2026

Submission Date

May 8, 2025

Acceptance Date

July 15, 2025

Published in Issue

Year 2026 Volume: 27 Number: 1

APA
Örgerim, A., & Kalkan, A. (2026). STOCK SENTIMENT ANALYSIS FROM NEWS HEADLINES BY USING ENSEMBLE BOOSTING ALGORITHMS. Doğuş Üniversitesi Dergisi, 27(1), 538-550. https://doi.org/10.31671/doujournal.1695398
AMA
1.Örgerim A, Kalkan A. STOCK SENTIMENT ANALYSIS FROM NEWS HEADLINES BY USING ENSEMBLE BOOSTING ALGORITHMS. Doğuş Üniversitesi Dergisi. 2026;27(1):538-550. doi:10.31671/doujournal.1695398
Chicago
Örgerim, Aslı, and Adnan Kalkan. 2026. “STOCK SENTIMENT ANALYSIS FROM NEWS HEADLINES BY USING ENSEMBLE BOOSTING ALGORITHMS”. Doğuş Üniversitesi Dergisi 27 (1): 538-50. https://doi.org/10.31671/doujournal.1695398.
EndNote
Örgerim A, Kalkan A (February 1, 2026) STOCK SENTIMENT ANALYSIS FROM NEWS HEADLINES BY USING ENSEMBLE BOOSTING ALGORITHMS. Doğuş Üniversitesi Dergisi 27 1 538–550.
IEEE
[1]A. Örgerim and A. Kalkan, “STOCK SENTIMENT ANALYSIS FROM NEWS HEADLINES BY USING ENSEMBLE BOOSTING ALGORITHMS”, Doğuş Üniversitesi Dergisi, vol. 27, no. 1, pp. 538–550, Feb. 2026, doi: 10.31671/doujournal.1695398.
ISNAD
Örgerim, Aslı - Kalkan, Adnan. “STOCK SENTIMENT ANALYSIS FROM NEWS HEADLINES BY USING ENSEMBLE BOOSTING ALGORITHMS”. Doğuş Üniversitesi Dergisi 27/1 (February 1, 2026): 538-550. https://doi.org/10.31671/doujournal.1695398.
JAMA
1.Örgerim A, Kalkan A. STOCK SENTIMENT ANALYSIS FROM NEWS HEADLINES BY USING ENSEMBLE BOOSTING ALGORITHMS. Doğuş Üniversitesi Dergisi. 2026;27:538–550.
MLA
Örgerim, Aslı, and Adnan Kalkan. “STOCK SENTIMENT ANALYSIS FROM NEWS HEADLINES BY USING ENSEMBLE BOOSTING ALGORITHMS”. Doğuş Üniversitesi Dergisi, vol. 27, no. 1, Feb. 2026, pp. 538-50, doi:10.31671/doujournal.1695398.
Vancouver
1.Aslı Örgerim, Adnan Kalkan. STOCK SENTIMENT ANALYSIS FROM NEWS HEADLINES BY USING ENSEMBLE BOOSTING ALGORITHMS. Doğuş Üniversitesi Dergisi. 2026 Feb. 1;27(1):538-50. doi:10.31671/doujournal.1695398