
# imdb_bertopic

This is a [BERTopic](https://github.com/MaartenGr/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:

```python
from bertopic import BERTopic
topic_model = BERTopic.load("davanstrien/imdb_bertopic")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 148
* Number of training documents: 103062

<details>
  <summary>Click here for an overview of all topics.</summary>
  
  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| -1 | film - movie - character - characters - very | 40 | -1_film_movie_character_characters | 
| 0 | movie - film - movies - acting - actors | 25087 | 0_movie_film_movies_acting | 
| 1 | episodes - shows - tv - television - watching | 2886 | 1_episodes_shows_tv_television | 
| 2 | bollywood - kapoor - hindi - indian - rani | 1945 | 2_bollywood_kapoor_hindi_indian | 
| 3 | horror - films - film - haunted - movies | 858 | 3_horror_films_film_haunted | 
| 4 | takashi - samurai - manga - anime - films | 800 | 4_takashi_samurai_manga_anime | 
| 5 | predator - alien - aliens - movie - film | 658 | 5_predator_alien_aliens_movie | 
| 6 | amelie - cinema - films - film - movie | 652 | 6_amelie_cinema_films_film | 
| 7 | nudity - porn - film - sexual - films | 647 | 7_nudity_porn_film_sexual | 
| 8 | mexican - film - spanish - movie - mexico | 619 | 8_mexican_film_spanish_movie | 
| 9 | comedies - comedy - humor - laughing - laughs | 589 | 9_comedies_comedy_humor_laughing | 
| 10 | homosexuality - queer - homosexual - sexuality - gay | 562 | 10_homosexuality_queer_homosexual_sexuality | 
| 11 | cary - cast - comedies - dunne - comedy | 459 | 11_cary_cast_comedies_dunne | 
| 12 | film - wwii - movie - patton - war | 408 | 12_film_wwii_movie_patton | 
| 13 | dracula - vampire - vampires - frankenstein - vlad | 405 | 13_dracula_vampire_vampires_frankenstein | 
| 14 | zombie - zombies - romero - undead - horror | 402 | 14_zombie_zombies_romero_undead | 
| 15 | kung - martial - chun - chan - fighter | 370 | 15_kung_martial_chun_chan | 
| 16 | soviet - stalin - moscow - russian - russians | 355 | 16_soviet_stalin_moscow_russian | 
| 17 | western - film - westerns - cast - wayne | 310 | 17_western_film_westerns_cast | 
| 18 | blacks - slavery - racism - racial - slaves | 308 | 18_blacks_slavery_racism_racial | 
| 19 | satanic - demon - satanist - devil - satan | 289 | 19_satanic_demon_satanist_devil | 
| 20 | jurassic - prehistoric - lost - dinosaur - dinosaurs | 241 | 20_jurassic_prehistoric_lost_dinosaur | 
| 21 | gameplay - rpg - games - adventure - game | 231 | 21_gameplay_rpg_games_adventure | 
| 22 | daffy - looney - bunny - cartoon - cartoons | 228 | 22_daffy_looney_bunny_cartoon | 
| 23 | bergman - films - swedish - henrik - film | 224 | 23_bergman_films_swedish_henrik | 
| 24 | movie - dogs - animals - film - puppies | 216 | 24_movie_dogs_animals_film | 
| 25 | hitchcock - thriller - suspense - film - films | 204 | 25_hitchcock_thriller_suspense_film | 
| 26 | criminal - criminals - film - crime - cop | 199 | 26_criminal_criminals_film_crime | 
| 27 | cinderella - disney - aladdin - fairy - anastasia | 191 | 27_cinderella_disney_aladdin_fairy | 
| 28 | films - film - movie - racing - racer | 188 | 28_films_film_movie_racing | 
| 29 | cinema - film - movie - actors - australian | 186 | 29_cinema_film_movie_actors | 
| 30 | natives - tribe - tribes - film - navajo | 184 | 30_natives_tribe_tribes_film | 
| 31 | jaws - shark - sharks - megalodon - movie | 174 | 31_jaws_shark_sharks_megalodon | 
| 32 | holocaust - auschwitz - schindler - nazi - nazis | 173 | 32_holocaust_auschwitz_schindler_nazi | 
| 33 | woodstock - concert - tour - documentary - stones | 170 | 33_woodstock_concert_tour_documentary | 
| 34 | adoption - abortion - ending - movie - daughter | 166 | 34_adoption_abortion_ending_movie | 
| 35 | bond - royale - connery - sutherland - craig | 161 | 35_bond_royale_connery_sutherland | 
| 36 | zhang - chinese - beijing - wong - films | 154 | 36_zhang_chinese_beijing_wong | 
| 37 | santa - scrooge - claus - christmas - carol | 152 | 37_santa_scrooge_claus_christmas | 
| 38 | messiah - biblical - gospel - jesus - film | 149 | 38_messiah_biblical_gospel_jesus | 
| 39 | sandler - gilmore - adam - comedies - comedy | 145 | 39_sandler_gilmore_adam_comedies | 
| 40 | woody - allen - wilder - bogart - movies | 142 | 40_woody_allen_wilder_bogart | 
| 41 | pacino - film - movie - actor - al | 142 | 41_pacino_film_movie_actor | 
| 42 | novel - book - books - movie - reading | 140 | 42_novel_book_books_movie | 
| 43 | yankee - yankees - baseball - ruth - 1961 | 138 | 43_yankee_yankees_baseball_ruth | 
| 44 | musicals - astaire - roberta - musical - irene | 136 | 44_musicals_astaire_roberta_musical | 
| 45 | gangster - gangsters - cagney - mafia - gangs | 135 | 45_gangster_gangsters_cagney_mafia | 
| 46 | actress - joan - crawford - film - movie | 134 | 46_actress_joan_crawford_film | 
| 47 | italian - italians - sicily - cinema - films | 127 | 47_italian_italians_sicily_cinema | 
| 48 | holmes - sherlock - doyle - watson - hound | 124 | 48_holmes_sherlock_doyle_watson | 
| 49 | slashers - movie - film - slasher - movies | 117 | 49_slashers_movie_film_slasher | 
| 50 | romance - movie - comedy - movies - romantic | 116 | 50_romance_movie_comedy_movies | 
| 51 | hogan - daredevil - hulk - daredevils - movies | 114 | 51_hogan_daredevil_hulk_daredevils | 
| 52 | werewolf - werewolves - wolf - wolfen - movie | 112 | 52_werewolf_werewolves_wolf_wolfen | 
| 53 | robin - flynn - films - hood - film | 110 | 53_robin_flynn_films_hood | 
| 54 | agatha - novels - novel - cast - marple | 108 | 54_agatha_novels_novel_cast | 
| 55 | netforce - supercomputer - security - hacking - computers | 104 | 55_netforce_supercomputer_security_hacking | 
| 56 | dragonball - goku - dragon - dragonheart - dragons | 104 | 56_dragonball_goku_dragon_dragonheart | 
| 57 | pirates - pirate - blackbeard - captain - film | 102 | 57_pirates_pirate_blackbeard_captain | 
| 58 | dancing - dance - dancer - choreography - dancers | 97 | 58_dancing_dance_dancer_choreography | 
| 59 | conspiracy - 911 - documentary - documentaries - pentagon | 94 | 59_conspiracy_911_documentary_documentaries | 
| 60 | chainsaw - massacre - slaughterhouse - movie - movies | 94 | 60_chainsaw_massacre_slaughterhouse_movie | 
| 61 | musical - soundtrack - film - movie - music | 93 | 61_musical_soundtrack_film_movie | 
| 62 | manhattan - burns - woody - films - sidewalks | 90 | 62_manhattan_burns_woody_films | 
| 63 | afghan - taliban - osama - film - movie | 89 | 63_afghan_taliban_osama_film | 
| 64 | turkish - turk - turks - turkey - kurdish | 89 | 64_turkish_turk_turks_turkey | 
| 65 | cannibalism - cannibal - cannibals - slaughterhouse - holocaust | 84 | 65_cannibalism_cannibal_cannibals_slaughterhouse | 
| 66 | movie - movies - kids - film - children | 82 | 66_movie_movies_kids_film | 
| 67 | hellraiser - hellraisers - hellworld - hellbound - hellboy | 82 | 67_hellraiser_hellraisers_hellworld_hellbound | 
| 68 | korean - korea - seoul - cinema - film | 81 | 68_korean_korea_seoul_cinema | 
| 69 | jedi - darth - prequels - skywalker - lightsaber | 81 | 69_jedi_darth_prequels_skywalker | 
| 70 | eddie - sequel - beverly - murphy - cop | 80 | 70_eddie_sequel_beverly_murphy | 
| 71 | fiona - irish - donegal - ireland - dublin | 79 | 71_fiona_irish_donegal_ireland | 
| 72 | beatles - ringo - mccartney - lennon - concert | 79 | 72_beatles_ringo_mccartney_lennon | 
| 73 | ninja - ninjas - kung - martial - cobra | 79 | 73_ninja_ninjas_kung_martial | 
| 74 | murder - prosecutor - innocent - justice - courtroom | 77 | 74_murder_prosecutor_innocent_justice | 
| 75 | lynch - mulholland - films - film - eraserhead | 76 | 75_lynch_mulholland_films_film | 
| 76 | godzilla - monster - monsters - shinoda - tokyo | 76 | 76_godzilla_monster_monsters_shinoda | 
| 77 | scorsese - film - films - comedy - goodfellas | 74 | 77_scorsese_film_films_comedy | 
| 78 | clancy - ryan - cia - director - thriller | 74 | 78_clancy_ryan_cia_director | 
| 79 | ringu - ring - prequel - sequel - film | 72 | 79_ringu_ring_prequel_sequel | 
| 80 | candyman - candy - tale - horror - movie | 70 | 80_candyman_candy_tale_horror | 
| 81 | guns - gun - shooting - bullets - lethal | 70 | 81_guns_gun_shooting_bullets | 
| 82 | claudius - roman - romans - emperors - emperor | 69 | 82_claudius_roman_romans_emperors | 
| 83 | jason - friday - 13th - movie - sequel | 69 | 83_jason_friday_13th_movie | 
| 84 | yugoslav - yugoslavian - bosnians - bosnian - croatians | 69 | 84_yugoslav_yugoslavian_bosnians_bosnian | 
| 85 | giallo - gialli - giallos - thriller - film | 68 | 85_giallo_gialli_giallos_thriller | 
| 86 | arthurian - arthur - merlin - medieval - excalibur | 68 | 86_arthurian_arthur_merlin_medieval | 
| 87 | robot - robots - robocop - asimov - film | 67 | 87_robot_robots_robocop_asimov | 
| 88 | thai - thailand - movie - bangkok - jungle | 67 | 88_thai_thailand_movie_bangkok | 
| 89 | batman - gotham - joker - superhero - comic | 67 | 89_batman_gotham_joker_superhero | 
| 90 | chaplin - comedies - films - film - circus | 67 | 90_chaplin_comedies_films_film | 
| 91 | superman - lois - reeve - clark - krypton | 67 | 91_superman_lois_reeve_clark | 
| 92 | marvel - wolverine - superhero - comics - cyclops | 66 | 92_marvel_wolverine_superhero_comics | 
| 93 | austen - novel - prejudice - emma - firth | 65 | 93_austen_novel_prejudice_emma | 
| 94 | movie - film - movies - future - time | 64 | 94_movie_film_movies_future | 
| 95 | doris - actress - ruth - judy - hollywood | 64 | 95_doris_actress_ruth_judy | 
| 96 | vhs - dvd - movie - film - movies | 63 | 96_vhs_dvd_movie_film | 
| 97 | corpses - flesh - cadavers - bodies - snatcher | 63 | 97_corpses_flesh_cadavers_bodies | 
| 98 | ants - ant - movie - wasp - wasps | 62 | 98_ants_ant_movie_wasp | 
| 99 | apostle - sermon - actor - duvall - preacher | 60 | 99_apostle_sermon_actor_duvall | 
| 100 | twins - twin - olsen - actresses - movie | 60 | 100_twins_twin_olsen_actresses | 
| 101 | tudors - tudor - anne - elizabeth - boleyn | 59 | 101_tudors_tudor_anne_elizabeth | 
| 102 | rocky - movie - film - tommy - rusty | 59 | 102_rocky_movie_film_tommy | 
| 103 | seagal - movie - movies - scenes - mercenary | 56 | 103_seagal_movie_movies_scenes | 
| 104 | film - documentary - witch - movies - movie | 56 | 104_film_documentary_witch_movies | 
| 105 | panther - clouseau - films - film - movies | 55 | 105_panther_clouseau_films_film | 
| 106 | van - cyborg - movie - film - arquette | 55 | 106_van_cyborg_movie_film | 
| 107 | freddy - nightmare - elm - horror - sequel | 54 | 107_freddy_nightmare_elm_horror | 
| 108 | crow - movie - film - films - angels | 53 | 108_crow_movie_film_films | 
| 109 | bambi - sequels - sequel - disney - movie | 53 | 109_bambi_sequels_sequel_disney | 
| 110 | potter - narnia - hogwarts - harry - dumbledore | 53 | 110_potter_narnia_hogwarts_harry | 
| 111 | puppetmaster - puppet - puppets - curse - magrew | 51 | 111_puppetmaster_puppet_puppets_curse | 
| 112 | germans - german - cinema - film - hans | 51 | 112_germans_german_cinema_film | 
| 113 | eastwood - harry - callahan - cop - dirty | 51 | 113_eastwood_harry_callahan_cop | 
| 114 | bruce - willis - movies - film - mcclane | 51 | 114_bruce_willis_movies_film | 
| 115 | dutch - dutchman - amsterdam - netherlands - holland | 50 | 115_dutch_dutchman_amsterdam_netherlands | 
| 116 | highlander - macleod - sequel - immortals - movie | 50 | 116_highlander_macleod_sequel_immortals | 
| 117 | clerks - comedy - film - movies - movie | 50 | 117_clerks_comedy_film_movies | 
| 118 | metalhead - metallica - metal - genres - genre | 50 | 118_metalhead_metallica_metal_genres | 
| 119 | angelopoulos - greek - trilogy - greece - tragedy | 50 | 119_angelopoulos_greek_trilogy_greece | 
| 120 | wilder - pryor - comedy - comedian - comedians | 49 | 120_wilder_pryor_comedy_comedian | 
| 121 | sopranos - soprano - tony - godfather - mafia | 48 | 121_sopranos_soprano_tony_godfather | 
| 122 | dracula - frankenstein - cat - poelzig - horror | 48 | 122_dracula_frankenstein_cat_poelzig | 
| 123 | myers - comedy - mike - guru - wayne | 48 | 123_myers_comedy_mike_guru | 
| 124 | comedy - lemmon - movie - cast - neil | 47 | 124_comedy_lemmon_movie_cast | 
| 125 | jezebel - scarlett - actress - warner - film | 47 | 125_jezebel_scarlett_actress_warner | 
| 126 | cast - crystal - mafia - comedies - movie | 47 | 126_cast_crystal_mafia_comedies | 
| 127 | marijuana - drug - pot - weed - marihuana | 47 | 127_marijuana_drug_pot_weed | 
| 128 | autism - autistic - charlie - movie - sam | 46 | 128_autism_autistic_charlie_movie | 
| 129 | sergio - corbucci - franco - mercenary - italian | 45 | 129_sergio_corbucci_franco_mercenary | 
| 130 | actress - acting - audrey - hollywood - griffith | 45 | 130_actress_acting_audrey_hollywood | 
| 131 | columbo - murderer - murder - detective - movie | 44 | 131_columbo_murderer_murder_detective | 
| 132 | egyptian - mohamed - egyptians - egypt - ahmed | 44 | 132_egyptian_mohamed_egyptians_egypt | 
| 133 | che - castro - ernesto - cuban - havana | 44 | 133_che_castro_ernesto_cuban | 
| 134 | horse - horses - thoroughbred - stallion - dakota | 44 | 134_horse_horses_thoroughbred_stallion | 
| 135 | costello - abbott - comedy - comedians - films | 43 | 135_costello_abbott_comedy_comedians | 
| 136 | conchita - surrealistic - surrealism - actresses - surrealist | 43 | 136_conchita_surrealistic_surrealism_actresses | 
| 137 | lindsay - movie - actress - film - teenage | 43 | 137_lindsay_movie_actress_film | 
| 138 | mummy - mummies - tomb - archaeologist - film | 42 | 138_mummy_mummies_tomb_archaeologist | 
| 139 | ebola - virus - movie - epidemic - film | 42 | 139_ebola_virus_movie_epidemic | 
| 140 | anaïs - anais - erotica - film - fiction | 42 | 140_anaïs_anais_erotica_film | 
| 141 | mormon - lds - mormons - brigham - missionaries | 42 | 141_mormon_lds_mormons_brigham | 
| 142 | chuck - chucks - norris - karate - fights | 42 | 142_chuck_chucks_norris_karate | 
| 143 | beowulf - grendel - hrothgar - siegfried - gaiman | 41 | 143_beowulf_grendel_hrothgar_siegfried | 
| 144 | martin - rigby - comedy - film - noir | 41 | 144_martin_rigby_comedy_film | 
| 145 | troma - tromeo - keoma - film - movie | 41 | 145_troma_tromeo_keoma_film | 
| 146 | airplane - passengers - airlines - plane - pilot | 41 | 146_airplane_passengers_airlines_plane |
  
</details>

## Training hyperparameters

* calculate_probabilities: False
* language: None
* low_memory: False
* min_topic_size: 40
* n_gram_range: (1, 1)
* nr_topics: None
* seed_topic_list: None
* top_n_words: 10
* verbose: False

## Framework versions

* Numpy: 1.22.4
* HDBSCAN: 0.8.29
* UMAP: 0.5.3
* Pandas: 1.5.3
* Scikit-Learn: 1.2.2
* Sentence-transformers: 2.2.2
* Transformers: 4.29.2
* Numba: 0.56.4
* Plotly: 5.13.1
* Python: 3.10.11
{"language": ["en"], "library_name": "bertopic", "tags": ["bertopic"], "datasets": ["imdb"], "pipeline_tag": "text-classification"}
bertopic text-classification en dataset:imdb region:us
TAGS
#bertopic #text-classification #en #dataset-imdb #region-us 

imdb\_bertopic
==============


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:


You can use the model as follows:


Topic overview
--------------


* Number of topics: 148
* Number of training documents: 103062



Click here for an overview of all topics.


Training hyperparameters
------------------------


* calculate\_probabilities: False
* language: None
* low\_memory: False
* min\_topic\_size: 40
* n\_gram\_range: (1, 1)
* nr\_topics: None
* seed\_topic\_list: None
* top\_n\_words: 10
* verbose: False


Framework versions
------------------


* Numpy: 1.22.4
* HDBSCAN: 0.8.29
* UMAP: 0.5.3
* Pandas: 1.5.3
* Scikit-Learn: 1.2.2
* Sentence-transformers: 2.2.2
* Transformers: 4.29.2
* Numba: 0.56.4
* Plotly: 5.13.1
* Python: 3.10.11



TAGS
#bertopic #text-classification #en #dataset-imdb #region-us 
