Updated readme from the GitHub page

README.md

@@ -1,14 +1,67 @@
----
-license: mit
-task_categories:
-- text-classification
-language:
-- lv
-tags:
-- sentiment
-- sentiment analysis
-- sentiment classification
-pretty_name: Latvian Twitter Eater Corpus - Sentiment
-size_categories:
-- 1K<n<10K
----
+---
+license: mit
+task_categories:
+- text-classification
+language:
+- lv
+tags:
+- sentiment
+- sentiment analysis
+- sentiment classification
+- Latvian
+- Twitter
+- social media
+- short text
+pretty_name: Latvian Twitter Eater Corpus - Sentiment
+size_categories:
+- 1K<n<10K
+---
+
+
+
+
+
+# Latvian Twitter Eater Corpus - Sentiment Analysis Sub-corpus
+
+This sub-corpus contains 5420 tweets with human-annotated sentiment as positive (pos), neutral (neu) or negative (neg). 1631 tweets are positive, 2507 - neutral and 1282 - negative.
+
+- **ltec-sentiment-annotated.json** contains tweets with human annotated sentiment
+- **ltec-sentiment-annotated-test.json** contains the test set that we used in our paper
+- **ltec-sentiment-automatic.json** contains tweets with automatically assigned sentiment based on emoticons
+
+## Tweet Structure
+```json
+{   
+	"sentiment":"pos",
+	"screen_name":"artisare",
+	"tweet_id":221520985738846209,
+	"tweet_text":"@mazheks Burgā ir brančs?!? Es jau sāku domāt ka uz Pērli jāmauc ēst pirms tam Illy paķerot kafiju. Cikos domā?"
+}
+```
+
+
+## Other Latvian twitter sentiment corpora
+---------
+* [Pinnis](https://github.com/pmarcis/latvian-tweet-corpus) - ~ 7000 tweets from politicians and companies
+* [Peisenieks](https://github.com/FnTm/latvian-tweet-sentiment-corpus) - ~ 1000 general tweets with sentiment annotated by multiple annotators
+* [Vīksna](https://github.com/RinaldsViksna/sikzinu_analize) - ~ 4000 general tweets
+* [Nicmanis](https://github.com/nicemanis/LV-twitter-sentiment-corpus) - ~ 2000 general tweets
+* [Špats](https://github.com/gatis/om) - ~ 6000 general tweets (lowercased)
+
+
+Publications
+---------
+
+If you use this corpus or scripts, please cite the following paper:
+
+Uga Sproģis and Matīss Rikters (2020). "[What Can We Learn From Almost a Decade of Food Tweets.](https://arxiv.org/abs/2007.05194)" In Proceedings of the 9th Conference Human Language Technologies - The Baltic Perspective ([Baltic HLT 2020](https://klc.vdu.lt/hlt/programme)) (2020).
+
+```bibtex
+@inproceedings{SprogisRikters2020BalticHLT,
+	author = {Sproģis, Uga and Rikters, Matīss},
+	booktitle={In Proceedings of the 9th Conference Human Language Technologies - The Baltic Perspective (Baltic HLT 2020)},
+	title = {{What Can We Learn From Almost a Decade of Food Tweets}},
+	address={Kaunas, Lithuania},
+	year = {2020}
+}
+```