Multidisciplinary Journal of Science and Technology

SENTIMENT ANALYSIS OF LATEST NEWS FROM QALAMPIR.UZ (FEBRUARY-MARCH)

Z.U.Kulmatov

Institute of International School of Finance Technology and Science (ISFT) Teacher of English, Master’s Philology and Language Teaching Department

---

Abstract

This study presents a sentiment analysis of news articles manually extracted from the English-language section of the Qalampir.uz website, covering the period from February to March. By applying natural language processing techniques, the study classifies the sentiment of news headlines into three categories: positive, negative, and neutral. The findings indicate that the majority of news content is neutral, with a notable presence of both positive and negative news items. These results provide insights into the tone and focus of recent media coverage in Uzbekistan and contribute to the broader field of computational journalism (Pang & Lee, 2008).

---

References

Bollen, J., Mao, H., & Zeng, X. (2011). Twitter mood predicts the stock market. Journal of Computational Science, 2(1), 1-8.

Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805.

Entman, R. M. (2007). Framing bias: Media in the distribution of power. Journal of Communication, 57(1), 163-173.

Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage.

González-Bailón, S., Banchs, R. E., & Kaltenbrunner, A. (2013). The structure of political discussion networks: A model for the analysis of online deliberation. Journal of Information Technology & Politics, 10(1), 44-63.

Liu, B. (2012). Sentiment analysis and opinion mining. Synthesis lectures on human language technologies, 5(1), 1-167.

Manning, C. D., Raghavan, P., & Schütze, H. (2008). Introduction to information retrieval. Cambridge University Press.

McCombs, M. E., & Shaw, D. L. (1972). The agenda-setting function of mass media. Public Opinion Quarterly, 36(2), 176-187.

Pang, B., & Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2(1–2), 1-135.

Reis, J. C., Kwak, H., An, J., & Ribeiro, F. (2015). Beyond positive and negative: Learning the spectrum of news credibility on Twitter. In Proceedings of the International AAAI Conference on Web and Social Media.

Shoemaker, P. J., & Vos, T. P. (2009). Gatekeeping theory. Routledge.

Tetlock, P. C. (2007). Giving content to investor sentiment: The role of media in the stock market. Journal of Finance, 62(3), 1139-1168.

Tuchman, G. (1978). Making news: A study in the construction of reality. Free Press.