Tennis Interviews

Transcripts for tennis singles post-match press conferences for major tournaments between 2007 to 2015 (6,467 post-match press conferences).

Distributed together with: Tie-breaker: Using language models to quantify gender bias in sports journalism. Liye Fu, Cristian Danescu-Niculescu-Mizil, Lillian Lee IJCAI workshop on NLP meets Journalism, 2016.

Dataset details

Speaker-level information

Speakers in this dataset are tennis professional players, represented by their real names. As this dataset do not contain information about individual reporters, we use a single pseudo user with username “REPORTER” to represent them.

For each player, additional metadata include:

• gender: player gender

Utterance-level information

Each question or answer is viewed as an utterance. For each utterance, we provide:

• id: index of the utterance
• speaker: the speaker who authored the utterance
• conversation_id: id of the first utterance in the conversation this utterance belongs to
• reply_to: id of the utterance to which this utterance replies to (None if the utterance is not a reply)
• timestamp: time of the utterance
• text: textual content of the utterance

Metadata for each utterance include:

• is_answer: whether the utterance is an answer from a player
• is_question: whether the utterance is a question raised by a reporter
• pair_idx: index of the question-answer pair
• parsed: parsed version of the utterance text, represented as a SpaCy Doc

Conversational-level information

Each round of question-answer pair is considered as a conversation. Metadata associated with conversations include additional information about the match for which the post-match interview is held:

• match_id: id of the match in the original dataset
• opponent: opponent in the match (available only if the opponent has at least one interview recorded in our dataset)
• result: outcome of the match (1 indicates the player being interviewed has won the match; 0 otherwise)
• stage: stage of the tournament (e.g., ‘The Final’)
• tournament: tournament name
• tournament_type: type of the tournament, indicating tournament prestige
• player_ranking: ranking of the player at the time of the match

Usage

To download directly with ConvoKit:

>>> from convokit import Corpus, download
>>> corpus = Corpus(filename=download("tennis-corpus"))

For some quick stats:

>>> corpus.print_summary_stats()
Number of Speakers: 359
Number of Utterances: 163948
Number of Conversations: 81974

Additional note

Related links

1. Transcripts gathered from ASAP sports’ website.
2. Corresponding match information, such as game outcome and player ranking, are obtained from Tennis-Data. Since transcripts data and match results are matched by date and player last name, and we did not manually check for every match, it is possible to have a few matching errors.

Contact

Please email any questions to: lf383@cornell.edu (Liye Fu).