topic_modelling_football

This is a BERTopic model. BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets.

Usage

To use this model, please install BERTopic:

pip install -U bertopic

You can use the model as follows:

from bertopic import BERTopic
topic_model = BERTopic.load("riccardopresti99/topic_modelling_football")

topic_model.get_topic_info()

Topic overview

  • Number of topics: 14
  • Number of training documents: 350
Click here for an overview of all topics.
Topic ID Topic Keywords Topic Frequency Label
-1 tournament - competition - leaving - final - compete 16 -1_tournament_competition_leaving_final
0 video - games - football - players - experience 10 0_video_games_football_players
1 supporters - atmosphere - stadiums - football - create 48 1_supporters_atmosphere_stadiums_football
2 physiotherapists - injury - injuries - players - prevention 32 2_physiotherapists_injury_injuries_players
3 united - film - football - war - story 29 3_united_film_football_war
4 ronaldo - ability - scoring - aspiring - one 26 4_ronaldo_ability_scoring_aspiring
5 scandals - illegal - officials - within - concerns 26 5_scandals_illegal_officials_within
6 healthy - footballers - energy - supports - performance 25 6_healthy_footballers_energy_supports
7 strikers - striker - scoring - teammates - goals 25 7_strikers_striker_scoring_teammates
8 investors - stock - stocks - market - club 25 8_investors_stock_stocks_market
9 women - football - girls - equal - sport 25 9_women_football_girls_equal
10 serie - milan - league - inter - italian 23 10_serie_milan_league_inter
11 champions - league - european - club - uefa 22 11_champions_league_european_club
12 cup - world - fifa - held - trophy 18 12_cup_world_fifa_held

Training hyperparameters

  • calculate_probabilities: False
  • language: None
  • low_memory: False
  • min_topic_size: 10
  • n_gram_range: (1, 1)
  • nr_topics: None
  • seed_topic_list: None
  • top_n_words: 10
  • verbose: True

Framework versions

  • Numpy: 1.23.5
  • HDBSCAN: 0.8.29
  • UMAP: 0.5.3
  • Pandas: 1.5.3
  • Scikit-Learn: 1.2.2
  • Sentence-transformers: 2.2.2
  • Transformers: 4.26.1
  • Numba: 0.56.4
  • Plotly: 5.13.1
  • Python: 3.10.10
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