| e9t/nsmc |
259 |
|
0 |
0 |
about 9 years ago |
0 |
|
1 |
|
Python |
| Naver sentiment movie corpus |
| sovaai/sova-dataset |
82 |
|
0 |
0 |
over 3 years ago |
0 |
|
1 |
other |
|
| google-research-datasets/query-wellformedness |
63 |
|
0 |
0 |
over 7 years ago |
0 |
|
1 |
|
|
| 25,100 queries from the Paralex corpus (Fader et al., 2013) annotated with human ratings of whether they are well-formed natural language questions. |
| vincentzlt/textprep |
33 |
|
0 |
0 |
about 7 years ago |
0 |
|
0 |
mit |
Python |
| Textprep is an analyzing tool for both parallel and non-parallel corpus and its down-stream Natural Language Processing and Machine Translation tasks. It is designed especially for logographic languages such as Chinese and Japanese. |
| compsocial/CREDBANK-data |
30 |
|
0 |
0 |
about 7 years ago |
0 |
|
5 |
|
|
| Data to accompany the ICWSM 2015 paper "CREDBANK: A Large-scale Social Media Corpus With Associated Credibility Annotations" |
| binodmx/sinhala-songs-corpus |
18 |
|
0 |
0 |
almost 6 years ago |
0 |
|
0 |
|
|
| Sinhala songs corpus with 2270 Sinhala songs |
| zifeishan/cs224s-deepSpeech |
14 |
|
0 |
0 |
almost 12 years ago |
0 |
|
0 |
|
Python |
| CS224S Course Project |
| hoffman-prezioso-projects/Amazon_Review_Sentiment_Analysis |
8 |
|
0 |
0 |
over 10 years ago |
0 |
|
0 |
|
Python |
| Sentiment analysis using a corpus of 34.6 million Amazon reviews |
| dimalik/Hrate |
7 |
|
0 |
0 |
over 8 years ago |
0 |
|
0 |
other |
R |
| Hrate package for R |
| AmmarRashed/CLSA |
5 |
|
0 |
0 |
over 7 years ago |
0 |
|
0 |
|
Jupyter Notebook |
| Cross-Lingual Sentiment Analysis |
