SemEval 2017 Task 5 - Subtask 2 "Fine-Grained Sentiment Analysis on Financial News Headlines"

This repository contains the data and source code for subtask 2 "News Headlines" of task 5 in SemEval 2017, "Fine-Grained Sentiment Analysis on Financial Microblogs and News" (see task website). It consists of a collection of financially relevant news headlines which have been annotated for fine-grained sentiment.


Each message in Headline_Trialdata.json is annotated with the following information:

  1. id: unique ID of the instance in our data
  2. title: text content of the headline
  3. company: company that the sentiment relates to
  4. sentiment: a floating point value between -1 (very bearish/negative) and 1 (very bullish/positive) denoting the sentiment expressed towards company. 0 denotes neutral sentiment.


The annotations are licensed under the Creative Commons Attribution-Non-Commercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license. Please cite the SemEval 2017 task description paper for task 5 (once available) when using this dataset.

If you are interested in commercial use of these data, please [contact the SSIX consortium|].


These resources were created in the context of the SSIX project. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 645425.