Datasets:

michsethowusu
/

hausa-sentiments-corpus

Hausa stringlengths 10 498	sentiment stringclasses 2 values	__index_level_0__ int64 0 670k
Kuma lalle ne gidan Lahira shi ne mafi alheri ga wadanda suka yi takawa, shin fa, ba ku hankalta?	Negative	0
Gaskantawa da Yesu ma bangare ne na tuba.	Negative	1
Tafkin wutan nan kuwa shi ne mutuwa ta biyu.	Negative	2
A sunana, Za su fitar da aljannu.	Positive	3
Yahi Dhoka Duniya Chalati Hai Yahi Sara Game Hai,	Positive	4
Da sunana za su fitar da aljannu.	Positive	5
Ta bangaren magoya baya kuwa, watakila idan a da an sa musu shakku, to zuwan nasa ya rage musu wannan shakku da ke zukatansu," in ji Malam Sufi.	Negative	6
sunadarai yana da muhimmanci!	Positive	7
Ba hakan nan ake istinbadi da Al-Kur'ani ba sai abubuwa biyu sun tabbata: kafa dalilin tabbatar da Al-Kur'anin, sannan .	Negative	8
Ina kira ga masu hikima, alloli na dā,	Positive	9
"To, shin suna jiran wani abu face kamar misalin kwanukan waxanda suka shuxe daga gabaninsu?	Negative	10
Amma da lokaci mai zabura ya rubuta wannan, Mutanen Allah sun riga an shigar da.	Negative	11
A rayuwa babu wani abu da yake karawa hikimar da Allah (SWT) da ya ba ka inganci, kamar daukar dawainiya.	Negative	12
Kada ku manta yau cewa ku daga Tsohon Virginia!"	Positive	13
Shin ka taba ciyar da yamma tare da wani inshora mai sayarwa?"	Negative	14
Kuma Mu ne mafi kusanta gare shi daga ku, to, amma ku ba ku gani.	Negative	15
Fauzan yacigaba dacewa "tunda an zubama i'do kak'i fito damatar dazaka aura aidole sai anma hakan.	Negative	16
Ya yi wannan ta wurin mutuwa da kuma tashin.	Positive	17
Za ku san (mai kyau daga mummunan) lokacin da kuka kwantar da hankula, a zaman lafiya.	Positive	18
Mu kuma mun fi kusa da shi fiye da ku, amma ba kwa gani.	Negative	19
Sa'an nan kuma zo Yesu tare da su zuwa ga wurin da ake kira	Positive	20
Ina mutum, don haka sai na dubi Instagram kowane minti ashirin.	Positive	21
Ya girgixa kansa yaja tsaki yace"feenah wannan ba d'a,a bace kishigo ba sallama kuma saikinzo hr tsakiyarr d'aki kana zakiyi sallama inkin tarar ba kaya ajikina ba kumafa?	Negative	22
Sahabbansa za a don haka mai tsanani azabtar da Allah, idan	Negative	23
Sai Yesu ya ce: "Don me kuke gwada ni, ku munafukai?"	Negative	24
Shin kun kasance Mafakar Dabbobi,	Positive	25
Kuma yayin da shi ke duk da kyau da kuma mai kyau - bayan duk, Budapest ne mai kyau birni - don't sell yourself...	Positive	26
Kuka ta saka cikin makirci tace "tunda ka d'aurewa tsohuwar karuwar matar kan nan gindi ba dole ta raina ni ba marina fa tayi ta turani seda na fad'i" waro ido yayi kan ya d'ago ga shaati "kina da hankali kuwa?	Negative	27
Maimaita abin da kuka aikata a baya tare da tsofaffi da sabbin posts.	Negative	28
Kamar yadda yake ba mu labarin irin yadda ta kasance tsakanin Qaruna da mutanensa, inda suka ce masa; " Kada ka yi fahariya, lalle ne Allah ba ya son masu fahariya (da abin duniya).	Negative	29
Kar ku yawanta hantararsu ba kuna cin zalinsu kuji tsoron Allah.	Positive	30
Shin zai iya yuwuwa a kai ga martabar ubangijintaka? - Taskar Amsoshi - islamquest	Negative	31
Da tsada fa aka saye ku, kada ku zama bayin mutane.	Positive	32
Ke kadai din ne xaki iya xuwa ki sari kaya da kanki? "	Negative	33
Ba za ka ji wani 'ya'ya dariya da wasa a cikin Jahannama, domin babu yara a jahannama.	Negative	34
Ga mafi yawan aji, dukkan jami'o'in gwamnati takwas na Hong Kong suna amfani da Turanci.	Positive	35
Nan da nan ta koma London a matsayin sabuwar sarauniya.	Positive	36
Shi ke yadda Ina jin lokacin da ina flipping ta su twitter comments, duk abin da na ji shi ne ruwan sama	Negative	37
"Ko kuwa za mu yi riqo ne da gaskiya baiyananna da shiriya da haske da kuma hanya madaidaiciya?	Negative	38
Google ma suna hush-hush akan sa, don haka muna kan kanmu.	Negative	39
Duk abunda sukeyi a kunne Farhan da Shureim,inda Farhan yace "Shureim ka k'oshi?"	Negative	40
Juyawa yayi kadan ya dubeta akayi sa'a suka hada idanu,saiya saki murmushi yana maida kanshi ga titi,cikin tattausan muryarsa can qasa kamar wanda ya fara bacci yace	Positive	41
Bal'amu kuwa ya amsa wa jakin, "Ka sanya wani wawa da ni!	Negative	42
Mu na can mu na ta amsar tara daga hannunsu."	Positive	43
Na yi tunani, "a yanzu na fahimci yadda za a yada musulunci a Amurka da Turai."	Positive	44
Ka san amsar zuwa lambar bakwai, Jack? - Student zuwa wani dalibi	Negative	45
"Yaya kake da arziki, amma ba za ka iya saya iyali mai farin ciki ba."	Negative	46
Amma idan facts kuma statistics ne abin da ka bukata, za ka iya samun su a nan.	Positive	47
Idan ana so zan murkushe su tsakanin tuddai ta Makka."	Negative	48
Wadanda suka karyata rai madawwami a cikin Kristi zasu fuskanci hukunci da azaba na har abada a jahannama .	Negative	49
Ko kuwa za a tattara musu dukan kifayen teku don su ishe su?"	Negative	50
Girgiza mata kai tayi alamar a'a, "sa ki yayi a jirgi yace kizo gida zaiyi tafiya ko?"	Negative	51
Dokar ta tuna wa Isra'ilawa cewa su ajizai ne.	Negative	52
To, za Mu sauk'ak'e masa har ya kai ga tsanani.	Positive	53
Kuma ee, saboda haka mutane da yawa suna magana da harsuna da yawa, a zahiri, muna mamakin ... menene harsuna mafi mahimmanci na Indiya?	Positive	54
An ce Holm yana da wani sabon coci domin kowane karni tunda nan.	Positive	55
"Masu hannu da shuni su taimakawa bayin Allah wadanda basu da shi.	Positive	56
Azurfarsu da zinariyarsu ba za su iya cetonsu ba, a ranar fushin Ubangiji.	Negative	57
A wannan dare suna magana kuma suna cewa ba sa so su rasa abokansu mafi kyau.	Positive	58
Don haka ta wace hanya yake bi da za mu yi sata, daga gidan ubangijin ka, zinariya ko azurfa?	Negative	59
K'aramin tsaki Beeba taja tana fad'in "Dadina dake Sumayya ke banza ce!Idan ba dalili ba me zanyi da number mijinki?kinga ni kin hutar dani dama yanzu zance ya baki zanyi magana dake !	Negative	60
Ina ganin ya kamata ya kasance a shafin kowa, Patric.	Negative	61
Bayan ya san haramcin hakan a addini?"	Negative	62
To, idan sun juya, sai ka ce:	Negative	63
Ta ce: "Mungode Allah da dawowar Yusuf danmu a yau bayan tafiya jinya.	Positive	64
Kiran shine ayi wa'azin Bishara ga kowane halitta.	Positive	65
Haka nan, za a shigar da kwafin lantarki a littafin tare da NSE a ranar da aka buga littafin.	Negative	66
Sallama yayi, tun da ta dago ta kalle shi bata ce komai ba, shima daga sallamar be kuma cewa komai ba.	Positive	67
Barci yana da kyau, ya ce, kuma littattafai sun fi kyau.	Positive	68
Bayan ka gama da tace, danna Create ya cece ka halitta sãbuwa.	Positive	69
Kuma Mune mafi kusanta gare shi daga ku, to, amma ku baku gani.'	Negative	70
Duk wanda zai yi aiki a wannan rana zai mutu.	Negative	71
Idan ban ga adireshi da lambar waya ba, ban sani ba ko za ku kasance cikin kasuwanci mako mai zuwa.	Negative	72
"Kinga Anty kuyi masa yadda yake so, Allah yasa haka ne mafi alheri ita Asma'u sai ta hakura."	Positive	73
Hakika, ba zai iya zama mai yawa - ba ni da wadata ba, ka sani."	Negative	74
Gama ka mai da mutane kamar kifaye a cikin teku,Kamar abubuwa masu rarrafe da ba su da shugaba.	Negative	75
Dan dadi ne na rayuwar duniya, sannan gare mu za ku dawo kuma mu ba ku labarin abin da kuka aikata."	Positive	76
Don haka, wannan zai iya koma zuwa da rabonka daga gādo - your rabo daga abin da aka bari a baya.	Positive	77
Domin zan shiryar da wani sharri a kan mutanen Anatot: da shekarar da za su sha hukuncinsu. "	Negative	78
"Mun ga ka juya ka fuskarka a cikin sama.	Positive	79
Kuna da malami mafi kyau a duniya tare da ku a kowane lokaci - ball na golf .	Positive	80
"Matasan Najeriya ... kuna iya gani?	Positive	81
A cewar mallamin duk wanda ya wulakanta al-Qur'ani mai tsarki toh babu shakka ya kafurta.	Negative	82
David bã su tambayar yadda idan ya ke da hakkin wannan taimako.	Negative	83
Mun yi annabci da sunanka kuma mun fitar da aljannu da sunanka kuma mun yi al'ajibai da yawa da sunanka. '	Positive	84
Ta nuna Shi da yatsa jira kaji Anwar na lura da take taken ka kana son mayar dani irin su mufeeda da ke binka suna maka biyayya kana musu yanda kaga dama ko?	Negative	85
"Babu wani abu da sauri fiye da wannan na'ura; kome da sauki fiye da wannan na'ura!"	Negative	86
Shi zai zama shugaban duk wanda yake Gileyad."	Positive	87
Saboda tsabar bin son zuciya,	Positive	88
A wannan rana ce kowane annabi zai ji kunyar wahayinsa sa'ad da ya yi annabcin.	Negative	89
Sa'an nan a aya ta gaba, za mu ga cewa yana cikin jahannama.	Negative	90
A Italiya sun koka cewa ban ziyarci ba, amma ina da gida a Florence wanda zan ziyarci uku ko sau hudu a shekara.	Positive	91
Duk da yake mutane da yawa suna magana game da EU a matsayin aikin zaman lafiya, wannan yana faruwa.	Positive	92
Har zuwa lacin mutuwarsa, yana aiki ne da wata kungiya mai zaman kanta na kasa da kasa," inji shi.	Positive	93
Na gode kwarai... Na gwada komai ba tare da sakamako ba ..	Positive	94
Ko kuna son mayar da hankali ga wani wasa, kamar Texas Hold'em , duk dare?	Negative	95
Sai manzon Allah (s.a.w) ya tambaye shi: shin daya daga cikin iyayenka yana raye?	Negative	96
"Mutuwa ta zo wurin garinku, Sheriff.	Negative	97
Ashe, ka gani, idan ya kasance a kan shiriya?	Negative	98
Duk respect d'in da kake bani ashe na k'arya ne baka tausayin mace?"	Negative	99

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Hausa Sentiment Corpus

Dataset Description

This dataset contains sentiment-labeled text data in Hausa 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: 669,937
Positive sentiment: 353111 (52.7%)
Negative sentiment: 316826 (47.3%)

Dataset Structure

Data Fields

Text Column: Contains the original text in Hausa
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/hausa-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 Hausa
Cross-lingual sentiment analysis research
African language NLP model development

Citation

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

@dataset{hausa_sentiments_corpus,
  title={Hausa Sentiment Corpus},
  author={Mich-Seth Owusu},
  year={2025},
  url={https://huggingface.co/datasets/michsethowusu/hausa-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:

36 MB

Size of the auto-converted Parquet files:

36 MB

Number of rows:

669,937

Collection including michsethowusu/hausa-sentiments-corpus

Africa Sentiment Datasets

Collection

The collection contains sentiment-labeled text data for 42 African languages • 43 items • Updated 2 days ago