# Predicting the Effects of News Sentiments on the Stock Market

arXiv: https://arxiv.org/abs/1812.04199 · HTML: https://mlsanity.com/paper/1812.04199/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Dec 2018.

## Built on by (most cited first, 10 of 10)

- [Revolutionizing Finance with LLMs: An Overview of Applications and Insights](https://mlsanity.com/paper/2401.11641/) (2024)
- [Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading](https://mlsanity.com/paper/2105.12825/) (2021)
- [Effects of Daily News Sentiment on Stock Price Forecasting](https://mlsanity.com/paper/2308.08549/) (2023)
- [ESG-FTSE: A corpus of news articles with ESG relevance labels and use cases](https://mlsanity.com/paper/2405.20218/) (2024)
- [Efficacy of Large Language Models in Systematic Reviews](https://mlsanity.com/paper/2408.04646/) (2024)
- [OSN Dashboard Tool For Sentiment Analysis](https://mlsanity.com/paper/2206.06935/) (2022)
- [Profiling the news spreading barriers using news headlines](https://mlsanity.com/paper/2304.11088/) (2023)
- [EnrichEvent: Enriching Social Data with Contextual Information for Emerging Event Extraction](https://mlsanity.com/paper/2307.16082/) (2023)
- [Analyzing public sentiment to gauge key stock events and determine volatility in conjunction with time and options premiums](https://mlsanity.com/paper/2502.05403/) (2025)
- [BAR-Analytics: A Web-based Platform for Analyzing Information Spreading Barriers in News: Comparative Analysis Across Multiple Barriers and Events](https://mlsanity.com/paper/2503.24220/) (2025)

## Abstract (arXiv)

Stock market forecasting is very important in the planning of business activities. Stock price prediction has attracted many researchers in multiple disciplines including computer science, statistics, economics, finance, and operations research. Recent studies have shown that the vast amount of online information in the public domain such as Wikipedia usage pattern, news stories from the mainstream media, and social media discussions can have an observable effect on investors opinions towards financial markets. The reliability of the computational models on stock market prediction is important as it is very sensitive to the economy and can directly lead to financial loss. In this paper, we retrieved, extracted, and analyzed the effects of news sentiments on the stock market. Our main contributions include the development of a sentiment analysis dictionary for the financial sector, the development of a dictionary-based sentiment analysis model, and the evaluation of the model for gauging the effects of news sentiments on stocks for the pharmaceutical market. Using only news sentiments, we achieved a directional accuracy of 70.59% in predicting the trends in short-term stock price movement.