Datasets:

michsethowusu
/

swahili-sentiments-corpus

Swahili stringlengths 9 487	sentiment stringclasses 2 values
Taifa wamebadili miungu yao, ingawa siyo miungu?	Negative
Yeye pia atakuwa taifa, naye pia atakuwa mkuu.	Positive
"Saa (kufika kiama) imekaribia; na mwezi umepasuka.	Negative
Au samaki wote wa baharini watakusanywa pamoja kwa ajili yao, ili kuwatosha?	Negative
Namna kila mumoja wao alifikia kuwa rafiki ya Mungu inaweza kutufundisha nini?	Negative
Je, unaweza kusema, "Ndiyo, nina uzima wa milele.	Positive
Kisha mmoja wao akasema: "Na miongoni mwetu yupo Mtume (Swalla Allaahu 'alayhi wa aalihi wa sallam) ambaye anajua yatakayotokea kesho.	Positive
Na kwa msaada wa Mungu, Yusufu anawaambia maana ya ndoto zao.	Positive
Mikono ya Yosefu mwenyewe ndiyo itakayofunga macho yako."	Positive
Hawa watu wetu wameshika miungu mingine badala yake Yeye.	Negative
Ukiwa kijana, huenda nyakati fulani ukaogopa kufuata amri za Mungu.	Negative
Akajibu, "Naam, na Imani ilikuwa ndani ya nyoyo zao kama milima."	Positive
takasika; na wao humo watadumu.	Positive
Yeye na wao walikuwa katika makabiliano ya kudumu maisha kati yao.	Negative
Na huu ni mwezi wa toba hakika atakuwa amenisamehe.	Positive
Na waulize habari za mji uliokuwa kando ya bahari.	Positive
Ukweli wa kifo unafahamika kwa uongofu wa Quran.	Positive
Kisha mikono ya wote walio pamoja nawe itatiwa nguvu."	Positive
wavulana, nimepata code ya kazi kutoka hapa!	Negative
Waumini hao tu ndio wangeingia mbinguni baada ya kifo, hii ina maana kuwa walikuwa wameokolewa.	Positive
Tunashukuru kama nini kwa sababu ya ujumbe wa Mungu ulio katika kitabu cha Isaya!	Positive
Atakula kila atakachokipata, na kama hatakipata, basi atakidai.	Negative
Je, unajua kile ambacho waliwapa watu wengine? - Kilikuwa kitu bora zaidi ulimwenguni!	Positive
naye atawapa Msaidizi Mwingine, ili akae nanyi hata milele."	Positive
Kama mtoto na baba yake yeye alitumika pamoja nami katika kuendeleza habari njema."	Positive
Au unadhani kwamba wengi wao wanasikia na wanafahamu?	Positive
Kwa yakini zilikuwepo katika (kisa cha) Yuwsuf na kaka zake Aayaat (ishara, dalili, zingatio) kwa waulizao.	Positive
Enyi mlio amini!Kwa nini mnasema msiyo yatenda?	Negative
Jina la huyo mwanamume ni nani, katika New Zealand, na mimi husahau kila wakati?	Negative
Wanangojea jingine ila kama yaliyotokea siku za watu walio pita kabla yao?	Negative
Lau Tungelitaka, Tungeliyafanya ya chumvi kali chungu basi kwa nini hamshukuru?	Negative
(Kwa kufanya kile unachokifanya sasa hivi, kujifunza neno la Mungu.	Positive
Kisha mapepo yakasema, "Hebu tufanye jambo jipya.	Positive
Basi huyo baba akagawanya mali yake kati yao.	Negative
Wanangojea jingine ila kama yaliyo tokea siku za watu walio pita kabla yao?	Negative
Akiwa Chanzo cha uhai, atakuwa Baba ya wote watakaofufuliwa.	Positive
Hata watenda-dhambi hufanya vivyo hivyo.	Negative
hatataka shauri kwa mwenye hekima.	Negative
na labda ndio sababu nitaondoka mara moja jua.	Negative
Hao ndio maadui, basi tahadhari nao.	Negative
Waambie wake zako: Ikiwa mnataka maisha ya dunia na pambo lake, basi	Positive
Akasema, Tangu utoto.	Positive
Wanyama au ardhi na jua pia vilionekana kati yao.	Positive
na jua hutambua wakati wake wa kutua.	Positive
kwa sababu ya uovu wa wale walioishi humo.	Negative
Hata wale bora katika wafuasi wake hawakuweza kuonyesha imani kweli.	Negative
Miji Itapatilizwa kwa Hukumu za Mungu Wakati umekaribia ambapo miji mikubwa itapatilizwa kwa hukumu za Mungu.	Positive
Roger ana yake blog mwenyewe, pia!	Positive
kuwahubiria Waisraeli lakini hawakuwa kumsikiliza.	Positive
Ila sio kuingilia kumsaidia mmoja wao.	Negative
(Allaah) Husema: "Je, ingekuwaje kama wangeuona Moto wangu!?"	Negative
Hata wenye dhambi hufanya vivyo hivyo.	Negative
Humo watakuwa na maskani ya kudumu, ndiyo malipo yao	Positive
Katika nyakati za kale, watumishi washikamanifu wa Mungu walisema au kufanya mambo yaliyowaumiza wengine.	Positive
Hakika yeye alidhani hatarejea.	Negative
Na wakaenda asubuhi hali wanadhani kuwa wanao uwezo wa kuzuia (masikini).	Positive
Je, hatutakuwa salama kwa kufuata kielelezo cha Baba na Mwana?	Negative
Hauko peke yako; bado kuna watu wengi wanaomwamini Mungu.	Positive
Wale wanaoyajua maisha ya Mtume watalifahamu hilo vyema zaidi.	Positive
Po pote waishipo amekufanya wewe kuwa mtawala juu yao wote.	Positive
Je, unafikiri kwamba upendo la Petro ulikuwa halisi wakati huo?	Negative
hakika udongo (mchanga) ulio safi ni tahara ya muislamu hata kama hakupata maji kwa miaka kumi.	Positive
Hawwaa (Amani iwe juu yake), yeye ndiye wa mwanzo kuipata.	Positive
Bali wao wamo katika shaka tu juu ya umbo jipya.	Negative
Na tulihitaji msaada kutoka mbinguni."	Negative
Danieli atafufuliwa wakati wa ufufuo wa waadilifu	Positive
Amri ya kwanza ya Amri Kumi inawataka watu kumwabudu Mungu wa kweli tu.	Negative
hakuna waliobarikiwa kuliko ninyi, hili kundi la watu.	Positive
Nimekutegemea Wewe tangu kuzaliwa,	Positive
Basi akawakubali katika jambo hili, akawathibitisha kwa siku kumi.	Positive
Alisema hivi: "Katika nyumba ya Baba yangu mna makao mengi.	Positive
Huyo hakika alidhani kuwa hatarejea tena.	Negative
huu ndio utakuwa mwonekano wa umma wa Jua la haki.	Positive
Nina wasiwasi kuhusu kupoteza muda wangu bora nchini Hispania sasa.	Negative
Sema: Sijui kama yapo karibu hayo mnayo ahidiwa, au	Negative
"Sisi pia tunaweza kuishi maisha mapya.")	Positive
Nitafanya ukumbusho wao usahauliwe kabisa miongoni mwa wanadamu,"	Negative
"Si rahisi kuwa ndiwe wa mwisho wa aina yako katika sayari yetu.	Negative
"Watu wanakuuliza kuhusu Saa.	Negative
(Katika baadhi ya sehemu za Afrika, wanasema, 'Mke mmoja - tatizo moja.	Negative
Tangu sasa na kuendelea utakuwa ukiwavua watu wakiwa hai."	Positive
Mkutano na kuoa msichana wa Kichina ni kitu mimi kujua mengi kuhusu.	Positive
"Wale wafanyao hayo (kuwapiga wake zao) si wabora wenu."	Negative
Naam; si kwa njia ya watu wa Mungu kuishi humo,	Negative
"Hapo Yusufu hakuweza kujizuia mbele yao wote waliosimama karibu naye.	Positive
na divai yangu mpya wakati itakapokuwa tayari.	Positive
nayo jumuiya yao itaimarishwa mbele yangu;	Positive
Iko wapi, basi, nyumba ambayo ninyi mnaweza kunijengea, na pako wapi, basi, mahali pa kupumzika kwa ajili yangu?"	Negative
Na wana wa Amoni wakakusanyika kutoka miji yao, wakaja vitani.	Positive
Je, utachagua kuwa miongoni mwa wenye haki?	Negative
Na alikwisha wajieni Yusuf zamani kwa dalili zilizo wazi, lakini nyinyi	Negative
Vivyo hivyo, watu wa Mungu leo hawafundishi maoni yao wenyewe.	Negative
Unataka neno la wazi, rahisi, moja kwa moja kutoka kwa Bwana leo?	Negative
Macho yangu yatawaelekea waaminifu katika nchi,	Positive
Watu kama hao wataishi milele katika mwangaza wa Mungu.	Positive
Na labda ulipendezwa na baraka fulani za Ufalme wa Mungu za wakati unaokuja zenye zilizungumuziwa katika habari hizo.	Positive
Kwa maana maagizo haya nikuagizayo leo, si mazito mno kwako, wala si mbali.	Positive
(Suala si ndoa mbinguni, bali ni ufufuo.	Positive
Kupitia hii, tunakuwa warithi wake, wale wanaorithi uzima wa milele, na mengi zaidi.	Positive
Lakini Philo alipofafanua utu wa Mungu Mweza-Yote, alienda mbali sana na ukweli.	Negative

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Swahili Sentiment Corpus

Dataset Description

This dataset contains sentiment-labeled text data in Swahili for binary sentiment classification (Positive/Negative). Sentiments are extracted and processed from the English meanings of the sentences using DistilBERT for sentiment classification. The dataset is part of a larger collection of African language sentiment analysis resources.

Dataset Statistics

Total samples: 1,500,000
Positive sentiment: 808179 (53.9%)
Negative sentiment: 691821 (46.1%)

Dataset Structure

Data Fields

Text Column: Contains the original text in Swahili
sentiment: Sentiment label (Positive or Negative only)

Data Splits

This dataset contains a single split with all the processed data.

Data Processing

The sentiment labels were generated using:

Model: distilbert-base-uncased-finetuned-sst-2-english
Processing: Batch processing with optimization for efficiency
Deduplication: Duplicate entries were removed based on text content
Filtering: Only Positive and Negative sentiments retained for binary classification

Usage

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("michsethowusu/swahili-sentiments-corpus")

# Access the data
print(dataset['train'][0])

# Check sentiment distribution
from collections import Counter
sentiments = [item['sentiment'] for item in dataset['train']]
print(Counter(sentiments))

Use Cases

This dataset is ideal for:

Binary sentiment classification tasks
Training sentiment analysis models for Swahili
Cross-lingual sentiment analysis research
African language NLP model development

Citation

If you use this dataset in your research, please cite:

@dataset{swahili_sentiments_corpus,
  title={Swahili Sentiment Corpus},
  author={Mich-Seth Owusu},
  year={2025},
  url={https://huggingface.co/datasets/michsethowusu/swahili-sentiments-corpus}
}

License

This dataset is released under the MIT License.

Contact

For questions or issues regarding this dataset, please open an issue on the dataset repository.

Dataset Creation

Date: 2025-07-02 Processing Pipeline: Automated sentiment analysis using HuggingFace Transformers Quality Control: Deduplication, batch processing optimizations, and binary sentiment filtering applied

Downloads last month: 0

Size of downloaded dataset files:

72.3 MB

Size of the auto-converted Parquet files:

72.3 MB

Number of rows:

1,500,000

Collection including michsethowusu/swahili-sentiments-corpus

Africa Sentiment Datasets

Collection

The collection contains sentiment-labeled text data for 42 African languages • 43 items • Updated 3 days ago