TweetsCOV19 - A Semantically Annotated Corpus of Tweets About the COVID-19 Pandemic (Part 1, October 2019 - April 2020)

The following list indicate the feature indices: Tweet Id: Long. Username: String. Encrypted for privacy issues*.

Timestamp: Format ( "EEE MMM dd HH:mm:ss Z yyyy" ). #Followers: Integer. #Friends: Integer. #Retweets: Integer. #Favorites: Integer. Entities: String. For each entity, we aggregated the original text, the annotated entity and the produced score from FEL library.

Each entity is separated from another entity by char ";". Also, each entity is separated by char ":" in order to store "original_text:annotated_entity:score;". If FEL did not find any entities, we have stored "null;".

Sentiment: String. SentiStrength produces a score for positive (1 to 5) and negative (-1 to -5) sentiment. We splitted these two numbers by whitespace char " ".

Positive sentiment was stored first and then negative sentiment (i.e. "2 -1"). Mentions: String. If the tweet contains mentions, we remove the char "@" and concatenate the mentions with whitespace char " ".

If no mentions appear, we have stored "null;". Hashtags: String. If the tweet contains hashtags, we remove the char "#" and concatenate the hashtags with whitespace char " ".

If no hashtags appear, we have stored "null;". URLs: String: If the tweet contains URLs, we concatenate the URLs using ":-: ". If no URLs appear, we have stored "null;" This dataset consists of 8,151,524 tweets in total, posted by 3,664,518 users and reflects the societal discourse about COVID-19 on Twitter in the period of October 2019 until April 2020.

To extract the dataset from TweetsKB , we compiled a seed list of 268 COVID-19-related keywords .

• For the sake of privacy, we anonymize user IDs and we do not provide the text of the tweets.