Fostering Data Fluency: Building a Strong Data…
The importance of unstructured textual new data in analysis above fundamental data
Capturing information above fundamental data is increasingly becoming a necessity in the financial industry and well as many others.
We now have the ability to objectively measure the emotion, or ‘news sentiment’, converting qualitative information contained in news stories into quantifiable measures.
The ever growing volume of news data and need for businesses to utilize additional sources of analysis to traditional data lead to Sia Partners propose this News Sentiment Bot as solution to managing the end-to-end collection, storage, analysis and visualization of news articles.
Collection: scraping of news articles published for specified queries.
Storage: in a dedicated SQL database, allowing for a historical depository of the news articles scraped and analyzed.
Analysis: machine learning algorithms analyze articles to enrich them by estimating their sentiment and topics.
Visualization: a search engine to look for news articles and a dashboard to visualize the results of sentiment and topic analysis.
Language support: supports scraping of news and native sentiment analysis in both English and Simplified Chinese.
To learn more about Heka and its ecosystem