Overtone global News Impact + Sentiment Correlation to Stock Price data set, real-time sourced

We show the correlation between impact index of journalistic articles and relevant stock price trends in near real time. Example: Global English language news content on Tesla for 12 months, scored by impact and sentiment, and indexed to Tesla (TSLA) stock price data for the same period. Data uniqueness: we use custom built and trained NLP algorithms to assess qualitative metrics inherent in text content. We focus on what's in the text, not metadata such as publication or engagement. Our AI algorithms are co-created by NLP & journalism experts. Our datasets have all been human-reviewed and labeled. Dataset: CSV containing URL and/or body text, with attributed scoring and sentiment values as integers, and model confidence as a percentage. Stock price data (daily open, close, high, low, avg) from NASDAQ. Other markets on request. We ignore metadata such as author, publication, date, word count, shares and so on, to provide a clean and maximally unbiased assessment of content. Our data is provided in CSV/RSS/JSON format. One row = one scored article. CSV contains URL and/or body text, with attributed scoring as an integer and model confidence as a percentage. News impact indicators provided as integers on a +1 to +5 scale. Sentiment shown on a -1 to +1 scale. Stock price values shown in USD, with deltas in % or absolute. Data sourcing: public websites, crawlers, scrapers, other partnerships where available. We generally can assess content behind paywalls as well as without paywalls. We source from ~4,000 news outlets, examples include: Bloomberg, CNN, BCC are one outlet each. Countries: all English-speaking markets world-wide. Includes English-language content from non English majority regions, such as Germany, Scandinavia, Japan. Also available in Spanish on request. Use-cases: assessing news source impact on the stock prices. Analysing buy/sell indicators based on publicly available (news) articles. We have shown correlation between news impact and indexed stock price changes. Clients also use this to decide on PR, media and marketing campaigns, for instance by partnering with the most impactful publishers, aggregators and syndicators of news content. Overtone provides a range of qualitative metrics for journalistic, newsworthy and long-form content. We find, highlight and synthesise content that shows added human effort and, by extension, added human value. This value can be direct to the reader, or for trading algorithms.

搜集汇总

背景与挑战

背景概述

该数据集利用定制NLP算法量化新闻文章的情感值（-1至+1）和影响力指数（1-5），并与对应股票（如特斯拉）的NASDAQ价格数据实时关联。数据以CSV/RSS/JSON格式提供，涵盖4000余家全球英文媒体，适用于金融舆情分析和交易策略制定。