|
--- |
|
license: cc |
|
task_categories: |
|
- text-classification |
|
language: |
|
- en |
|
tags: |
|
- tweet-classification |
|
- topic-detection |
|
- topic-classification |
|
- topics |
|
- tweets |
|
- tweet-length |
|
--- |
|
|
|
Published tweet dataset used in "Tweet Length Matters: A Comparative Analysis on Topic Detection in Microblogs" includes tweet id and corresponding topic number. |
|
|
|
Topic numbers encoded as follows: |
|
|
|
Topic Topic Number |
|
BLM Movement 0 |
|
Covid-19 1 |
|
K-Pop 2 |
|
Bollywood 3 |
|
Gaming 4 |
|
U.S. Politics 5 |
|
Out-of-Topic 6 |
|
|
|
In total, there are 354,310 tweet instances. |
|
|
|
More details can be found at https://github.com/avaapm/ECIR2021/ |
|
|
|
Citation |
|
|
|
If you make use of these tools, please cite following paper. |
|
|
|
@inproceedings{DBLP:conf/ecir/SahinucT21, |
|
author = {Furkan {\c{S}}ahinu{\c{c}} and Cagri Toraman}, |
|
title = {Tweet Length Matters: {A} Comparative Analysis on Topic Detection in Microblogs}, |
|
booktitle = {Advances in Information Retrieval - 43rd European Conference on {IR} Research, {ECIR} 2021, Virtual Event, March 28 - April 1, 2021, Proceedings, Part {II}}, |
|
series = {Lecture Notes in Computer Science}, |
|
volume = {12657}, |
|
pages = {471--478}, |
|
publisher = {Springer}, |
|
year = {2021}, |
|
url = {https://doi.org/10.1007/978-3-030-72240-1\_50}, |
|
doi = {10.1007/978-3-030-72240-1\_50}, |
|
} |
