bibtex

README.md

@@ -25,12 +25,22 @@ pretty_name: Polish-Political-Advertising
 
 Political campaigns are full of political ads posted by candidates on social media. Political advertisement constitute a basic form of campaigning, subjected to various social requirements. We present the first publicly open dataset for detecting specific text chunks and categories of political advertising in the Polish language. It contains 1,705 human-annotated tweets tagged with nine categories, which constitute campaigning under Polish electoral law.
 
-> We achieved a 0.65 inter-annotator agreement (Cohen's kappa score). An additional annotator resolved the mismatches between the first two annotators improving the consistency and complexity of the annotation process. ##
+> We achieved a 0.65 inter-annotator agreement (Cohen's kappa score). An additional annotator resolved the mismatches between the first two annotators improving the consistency and complexity of the annotation process.
 
 ### Citing
 
 > ACL WiNLP 2020 Paper
 
-```
-@inproceedings{augustyniak-etal-2020-political, title = "Political Advertising Dataset: the use case of the Polish 2020 Presidential Elections", author = "Augustyniak, Lukasz and Rajda, Krzysztof and Kajdanowicz, Tomasz and Bernaczyk, Micha{\l}", booktitle = "Proceedings of the The Fourth Widening Natural Language Processing Workshop", month = jul, year = "2020", address = "Seattle, USA", publisher = "Association for Computational Linguistics", url = "https://www.aclweb.org/anthology/2020.winlp-1.28", pages = "110--114" }
+```bibtex
+@inproceedings{augustyniak-etal-2020-political,
+    title = "Political Advertising Dataset: the use case of the Polish 2020 Presidential Elections",
+    author = "Augustyniak, Lukasz and Rajda, Krzysztof and Kajdanowicz, Tomasz and Bernaczyk, Micha{\l}",
+    booktitle = "Proceedings of the The Fourth Widening Natural Language Processing Workshop",
+    month = jul,
+    year = "2020",
+    address = "Seattle, USA",
+    publisher = "Association for Computational Linguistics",
+    url = "https://www.aclweb.org/anthology/2020.winlp-1.28",
+    pages = "110--114"
+}
 ```