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