{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/predicting-the-effects-of-news-sentiments-on","title":"Predicting the Effects of News Sentiments on the Stock Market","arxiv_id":"1812.04199","date":"2018-12-11","proceeding":null,"authors":["Dev Shah","Haruna Isah","Farhana Zulkernine"],"abstract":"Stock market forecasting is very important in the planning of business\nactivities. Stock price prediction has attracted many researchers in multiple\ndisciplines including computer science, statistics, economics, finance, and\noperations research. Recent studies have shown that the vast amount of online\ninformation in the public domain such as Wikipedia usage pattern, news stories\nfrom the mainstream media, and social media discussions can have an observable\neffect on investors opinions towards financial markets. The reliability of the\ncomputational models on stock market prediction is important as it is very\nsensitive to the economy and can directly lead to financial loss. In this\npaper, we retrieved, extracted, and analyzed the effects of news sentiments on\nthe stock market. Our main contributions include the development of a sentiment\nanalysis dictionary for the financial sector, the development of a\ndictionary-based sentiment analysis model, and the evaluation of the model for\ngauging the effects of news sentiments on stocks for the pharmaceutical market.\nUsing only news sentiments, we achieved a directional accuracy of 70.59% in\npredicting the trends in short-term stock price movement.","url_abs":"http://arxiv.org/abs/1812.04199v1","url_pdf":"http://arxiv.org/pdf/1812.04199v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"predicting-the-effects-of-news-sentiments-on","repo_url":"https://github.com/nicklamonica/stock-sentiment-analysis","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"sentiment-analysis","task_name":"Sentiment Analysis"},{"task_slug":"stock-market-prediction","task_name":"Stock Market Prediction"},{"task_slug":"stock-price-prediction","task_name":"Stock Price Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1812.04199","atlas_url":"https://app.syntology.ai/?focus=1812.04199","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}