Dataset Open Access

News Headline Sentiment Dataset

Chang Wei Tan; Christoph Bergmeir; Francois Petitjean; Geoffrey I Webb

This dataset is part of the Monash, UEA & UCR time series regression repository. http://timeseriesregression.org/

The goal of this dataset is to predict sentiment score for news headline. This dataset contains 83164 time series obtained from the News Popularity in Multiple Social Media Platforms dataset from the UCI repository. This is a large data set of news items and their respective social feedback on multiple platforms: Facebook, Google+ and LinkedIn. The collected data relates to a period of 8 months, between November 2015 and July 2016, accounting for about 100,000 news items on four different topics: economy, microsoft, obama and palestine. This data set is tailored for evaluative comparisons in predictive analytics tasks, although allowing for tasks in other research areas such as topic detection and tracking, sentiment analysis in short text, first story detection or news recommendation. The time series has 3 dimensions. 

Please refer to https://archive.ics.uci.edu/ml/datasets/News+Popularity+in+Multiple+Social+Media+Platforms for more details

Citation request
Nuno Moniz and Luis Torgo (2018), Multi-Source Social Feedback of Online News Feeds, CoRR

Files (73.9 MB)
Name Size
NewsHeadlineSentiment_TEST.ts
md5:e7b4c03f9846a6ada8d6bc8f3e0d6940
22.2 MB Download
NewsHeadlineSentiment_TRAIN.ts
md5:8d623413a0672043c234748f601009cf
51.7 MB Download
215
66
views
downloads
All versions This version
Views 215215
Downloads 6666
Data volume 2.6 GB2.6 GB
Unique views 188188
Unique downloads 5353

Share

Cite as