financial-machine-learning/generated_wiki/textual.md

| <sub>repo</sub>                                                                                                                                 | <sub>comment</sub>                                                                           | <sub>created_at</sub>          | <sub>last_commit</sub>         | <sub>star_count</sub>   | <sub>repo_status</sub>              | <sub>rating</sub>   |
|:------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------|:-------------------------------|:-------------------------------|:------------------------|:------------------------------------|:--------------------|
| <sub>[NLP](https://github.com/toamitesh/NLPinFinance)</sub>                                                                                     | <sub>This project assembles a lot of NLP operations needed for finance domain.</sub>         | <sub>nan</sub>                 | <sub>nan</sub>                 | <sub>nan</sub>          | <sub>:heavy_check_mark:</sub>       | <sub></sub>         |
| <sub>[Extensive NLP](https://github.com/TiesdeKok/Python_NLP_Tutorial/blob/master/NLP_Notebook.ipynb)</sub>                                     | <sub>Comprehensive NLP techniques for accounting research.</sub>                             | <sub>2017-10-25 07:10:26</sub> | <sub>2020-06-05 03:28:46</sub> | <sub>86.0</sub>         | <sub>:heavy_check_mark:</sub>       | <sub></sub>         |
| <sub>[NLP Event](https://github.com/yuriak/DLQuant)</sub>                                                                                       | <sub>Applying Deep Learning and NLP in Quantitative Trading.</sub>                           | <sub>2018-07-02 23:50:52</sub> | <sub>2019-01-31 14:08:20</sub> | <sub>77.0</sub>         | <sub>:heavy_multiplication_x:</sub> | <sub></sub>         |
| <sub>[Fund classification](https://github.com/frechfrechfrech/Mutual-Fund-Market-Clusters/blob/master/Initial%20Data%20Exploration.ipynb)</sub> | <sub>Fund classification using text mining and NLP.</sub>                                    | <sub>2018-04-16 22:18:55</sub> | <sub>2018-06-07 22:01:32</sub> | <sub>6.0</sub>          | <sub>:heavy_multiplication_x:</sub> | <sub></sub>         |
| <sub>[Financial Sentiment Analysis](https://github.com/EricHe98/Financial-Statements-Text-Analysis)</sub>                                       | <sub>Sentiment, distance and proportion analysis for trading signals.</sub>                  | <sub>2017-06-23 00:05:49</sub> | <sub>2019-01-26 03:35:55</sub> | <sub>54.0</sub>         | <sub>:heavy_multiplication_x:</sub> | <sub></sub>         |
| <sub>[Earning call transcripts](https://github.com/lin882/WebAnalyticsProject)</sub>                                                            | <sub>Correlation between mutual fund investment decision and earning call transcripts.</sub> | <sub>2017-12-30 08:56:03</sub> | <sub>2018-01-11 02:11:11</sub> | <sub>5.0</sub>          | <sub>:heavy_multiplication_x:</sub> | <sub></sub>         |
| <sub>[awesome-financial-nlp](https://github.com/icoxfog417/awesome-financial-nlp)</sub>                                                         | <sub>NEW</sub>                                                                               | <sub>2019-10-03 03:53:20</sub> | <sub>2020-02-01 08:28:16</sub> | <sub>264.0</sub>        | <sub>:heavy_check_mark:</sub>       | <sub></sub>         |
| <sub>[news-emotion](https://github.com/dongyuanxin/news-emotion)</sub>                                                                          | <sub>NEW</sub>                                                                               | <sub>2017-09-14 02:59:03</sub> | <sub>2018-06-11 13:47:51</sub> | <sub>262.0</sub>        | <sub>:heavy_multiplication_x:</sub> | <sub></sub>         |
| <sub>[FinNLP-Progress](https://github.com/YangLinyi/FinNLP-Progress)</sub>                                                                      | <sub>NEW</sub>                                                                               | <sub>2020-05-21 09:59:56</sub> | <sub>2021-09-30 08:26:25</sub> | <sub>222.0</sub>        | <sub>:heavy_check_mark:</sub>       | <sub></sub>         |
| <sub>[Buzzwords](https://github.com/swap9047/Cutting-Edge-Technologies-Effect-on-S-P500-Companies-Performance-and-Mutual-Funds)</sub>           | <sub>Return performance and mutual fund selection.</sub>                                     | <sub>2018-02-04 21:51:16</sub> | <sub>2018-02-04 21:57:09</sub> | <sub>2.0</sub>          | <sub>:heavy_multiplication_x:</sub> | <sub></sub>         |
| <sub>[financial-news-dataset](https://github.com/philipperemy/financial-news-dataset)</sub>                                                     | <sub>NEW</sub>                                                                               | <sub>2016-08-23 13:29:07</sub> | <sub>2021-03-04 06:34:24</sub> | <sub>160.0</sub>        | <sub>:heavy_check_mark:</sub>       | <sub></sub>         |
| <sub>[FinBERT](https://github.com/psnonis/FinBERT)</sub>                                                                                        | <sub>NEW</sub>                                                                               | <sub>2019-07-09 16:34:27</sub> | <sub>2020-05-19 02:02:20</sub> | <sub>156.0</sub>        | <sub>:heavy_check_mark:</sub>       | <sub></sub>         |
| <sub>[Accounting Anomalies](https://github.com/GitiHubi/deepAI/blob/master/GTC_2018_Lab-solutions.ipynb)</sub>                                  | <sub>Using deep-learning frameworks to identify accounting anomalies.</sub>                  | <sub>2017-05-24 12:36:38</sub> | <sub>2019-08-07 21:47:08</sub> | <sub>130.0</sub>        | <sub>:heavy_multiplication_x:</sub> | <sub></sub>         |
| <sub>[Financial Statement Sentiment](https://github.com/MAydogdu/TextualAnalysis)</sub>                                                         | <sub>Extracting sentiment from financial statements using neural networks.</sub>             | <sub>2018-06-04 20:54:14</sub> | <sub>2018-06-04 20:56:02</sub> | <sub>13.0</sub>         | <sub>:heavy_multiplication_x:</sub> | <sub></sub>         |
| <sub>[BDCI2019-Negative_Finance_Info_Judge](https://github.com/A-Rain/BDCI2019-Negative_Finance_Info_Judge)</sub>                               | <sub>NEW</sub>                                                                               | <sub>2019-12-27 03:49:31</sub> | <sub>2020-12-04 03:38:57</sub> | <sub>115.0</sub>        | <sub>:heavy_check_mark:</sub>       | <sub></sub>         |