https://github.com/candlewill/ordinal_classification
Ordinal Classification of Tweets
https://github.com/candlewill/ordinal_classification
Last synced: 12 months ago
JSON representation
Ordinal Classification of Tweets
- Host: GitHub
- URL: https://github.com/candlewill/ordinal_classification
- Owner: candlewill
- Created: 2016-01-25T14:51:51.000Z (over 10 years ago)
- Default Branch: master
- Last Pushed: 2016-04-07T09:27:55.000Z (about 10 years ago)
- Last Synced: 2025-03-11T11:34:35.259Z (over 1 year ago)
- Language: Python
- Size: 111 MB
- Stars: 1
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: readme.MD
Awesome Lists containing this project
README
### Ordinal Classification of Tweets
This project is the code for SemEval-2016 Task 4 sub-task C competition.
Task: Given a tweet known to be about a given topic, estimate the sentiment conveyed by the tweet towards the topic on a five-point scale.
### Data Description
|Name|Size|# Available (Percentage)|# Topics|#(-2)|#(-1)|#(0) |#(1)|#(2)|Max Length|Min Length|Average Length|
|------|------|------|------|------|------|------|------|------|------|------|------|
|Gold Train|6000|5346 (89.1%)|60|87|668|1654|3154|437|34|5|19.49|
|Gold Dev|2000|1795 (89.75%)|20|43|296|675|933|53|31|6|19.58|
|Gold Devtest|2000|1781 (89.05%)|20|31|233|583|1005|148|31|5|19.69|
|Input Devtest|2000|1781 (89.05%)|20|-|-|-|-|-|31|5|19.69|
Note: The "Not Available" terms are removed when gather statistics information of Max Length, Min Length, Average Length.
Number and Sentiment Intensity mapping method
|Sentiment Intensity|strongly negative|negative|negative or neutral|positive|strongly positive|
|------|------|------|------|------|------|
|Sentiment Score|-2|-1|0|1|2|
The topics in gold train, gold dev, gold devtest data: [topics](./MD/topics.MD). We can see that the topic in different data set is different. Exactly, there are no common topics between the three data set.
### Contact me
* [Yunchao He](https://plus.google.com/+YunchaoHe)
* yunchaohe@gmail.com
* [YZU](http://www.yzu.edu.tw/) at Taiwan
* [Weibo](http://weibo.com/heyunchao)
* [Facebook](https://www.facebook.com/yunchao.h)
* [Twitter](https://twitter.com/candlewill)
* @元智大学资讯工程学系1608B 民105年1月