MARTINI_enrich_BERTopic_heilukraine1959

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("AIDA-UPM/MARTINI_enrich_BERTopic_heilukraine1959")

topic_model.get_topic_info()

Topic overview

• Number of topics: 25
• Number of training documents: 3277

Click here for an overview of all topics.

Topic ID	Topic Keywords	Topic Frequency	Label
-1	ukrainians - putin - на - nato - armed	22	-1_ukrainians_putin_на_nato
0	nazies - holodomor - hooligans - lol - flags	1848	0_nazies_holodomor_hooligans_lol
1	الاسراييلي - الهجمات - الفلسطينية - gaza - الجيش	159	1_الاسراييلي_الهجمات_الفلسطينية_gaza
2	ukr - swastika - tanks - tattoo - reichslader	99	2_ukr_swastika_tanks_tattoo
3	ukrainians - latvians - odessa - speak - police	97	3_ukrainians_latvians_odessa_speak
4	zaporozhye - missiles - bayraktar - drone - crashed	82	4_zaporozhye_missiles_bayraktar_drone
5	ukrainians - refugees - warsaw - uninvited - harskamp	76	5_ukrainians_refugees_warsaw_uninvited
6	mariupol - militants - azovites - atrocities - battalion	75	6_mariupol_militants_azovites_atrocities
7	gaza - ramallah - netanyahu - genocide - airstrikes	75	7_gaza_ramallah_netanyahu_genocide
8	zelensky - trump - anatoli - clown - cokehead	75	8_zelensky_trump_anatoli_clown
9	putin - afghanistan - blinken - sanctions - serbia	72	9_putin_afghanistan_blinken_sanctions
10	الاوكرانية - الناتو - سوريا - الحرب - روسيا	68	10_الاوكرانية_الناتو_سوريا_الحرب
11	donetsk - bombing - civilians - stalingrad - munitions	66	11_donetsk_bombing_civilians_stalingrad
12	frankivsk - nazism - victory - memorial - brezhnev	65	12_frankivsk_nazism_victory_memorial
13	putin - crimean - kirill - jihadists - bogdan	64	13_putin_crimean_kirill_jihadists
14	украинец - russians - karabakh - maggots - pelmeni	51	14_украинец_russians_karabakh_maggots
15	subscribers - sputnik - notizie - trackanazimerc - suppressed	42	15_subscribers_sputnik_notizie_trackanazimerc
16	chernivtsi - khmelnitsky - persecution - priests - trebukhov	41	16_chernivtsi_khmelnitsky_persecution_priests
17	russians - нацистские - indoctrinated - азов - nigger	35	17_russians_нацистские_indoctrinated_азов
18	anthem - denazification - volhyn - warsaw - singer	35	18_anthem_denazification_volhyn_warsaw
19	kiev - priests - monastery - pechersk - orthodox	31	19_kiev_priests_monastery_pechersk
20	mercenaries - chernigov - ostashkonews - hector - bordon	28	20_mercenaries_chernigov_ostashkonews_hector
21	crimea - tiktoks - lutsenko - tankmen - vitalik	27	21_crimea_tiktoks_lutsenko_tankmen
22	conscripts - khmelnytsky - commissars - lvov - derazhnya	22	22_conscripts_khmelnytsky_commissars_lvov
23	severodonetsk - brigade - artillerymen - surrendered - militant	22	23_severodonetsk_brigade_artillerymen_surrendered

Training hyperparameters

• calculate_probabilities: True
• 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: False
• zeroshot_min_similarity: 0.7
• zeroshot_topic_list: None

Framework versions

• Numpy: 1.26.4
• HDBSCAN: 0.8.40
• UMAP: 0.5.7
• Pandas: 2.2.3
• Scikit-Learn: 1.5.2
• Sentence-transformers: 3.3.1
• Transformers: 4.46.3
• Numba: 0.60.0
• Plotly: 5.24.1
• Python: 3.10.12