Africa Sentiment Datasets
Collection
The collection contains sentiment-labeled text data for 42 African languages
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43 items
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Updated
Dataset Viewer
Yoruba
stringlengths 7
481
| sentiment
stringclasses 2
values |
|---|---|
kikase sugita ADORIBU to hikikae ni asu wa konai darou
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Negative
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onim o letu i moru,
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Positive
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Awon to gba iyanu lodo Olorun nikan o ba enu ilekun wole.
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Positive
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Igba yen nko, bawo ni mo ti fi han fun nyin?"
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Negative
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Oba t'O we adete mo (Ko s'oba meji af'Oluwa)
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Negative
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Olohun lo ni eto pe ki e beru Re, ti enyin ba je onigbagbo ododo).
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Positive
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Ati pe ti ko ba si ododo, nigbana ojiji Olorun lo wa mbe.
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Negative
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OSIEC Osun Taiwo Olodo
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Positive
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ni áinshun ni áinhun ni áinōhun
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Negative
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Otile, olodo!
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Positive
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if ala yaara nave ahipaad,
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Positive
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O ti funni ni idaniloju nkan yii si gbogbo eniyan nipa O ji dide kuro ninu oku. "
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Positive
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Oba t'o mo ohun gbogbo, (The all knowing God) Oba t'o mo ohun gbogbo, (il Dio onnisciente)
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Positive
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Saanse Jaye Aatak Aatak,
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Positive
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Kini a o se nigbati onigbagbo kan ba dede ku.
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Positive
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O tun so pe oun ko ti i setan lati ba wa soro, ati pe ti akoko oro ba to, oun yoo ranse si wa.
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Positive
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bali to aasiwan
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Positive
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ni èmi yóò fi ohun ìyanu hàn án."
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Positive
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Ti ko ba je wi pe awon eni ti a ni ko fe ni loju fata senu ni, kilo fe mu oju ti n gun ni tun maa tani bi ata.
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Negative
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Eyin ni ohun elo to po,ipo gidi.
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Positive
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Olúwa mi àmòimòtán.
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Positive
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Ati bakanna, w haven ti t afterlé àw godsn strangel strangerun àjòjì, ki nwon le ma sin won.
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Positive
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Wa Yusufeen wa be Ishaqeen wa gay re he mu, Min anbiyaeen
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Positive
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O tobi ju oun to tobiju, osi kere ju oun to kere ju.
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Positive
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O ko ba ri ohunkohun sugbon òkunkun.
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Positive
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Kii tan ninu igba osuun, k'ama fi r'amo Lori,
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Negative
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Tani ninu yin lati gbogbo eniyan re?
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Negative
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Yi ajinde ko ni waye si aye re.
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Positive
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Omó atanna Ifa yoro yoro lé kú lo Ikú ti nbe ni le yi kóderú kojade Owiri wiri a o fi iná Ifa wi wón lára
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Negative
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Mo ro, "bayi ni mo oye bi o lati tan Islam ni United States ati Europe."
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Positive
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Obesere Oye Olohun (God Knows Best)
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Positive
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Iwon't be online tonight!
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Negative
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Be tie bu won, ase Olorun ni, Olorun ti fun won ni ore ofe lati pa awon oruko yi re ni.
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Positive
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Wipe, ara eniyan o tobi wà.
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Positive
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Adegbulu AJ,
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Negative
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Gbogbo aye, gbe Jesu ga, Angel', e wole fun E mu ade Oba Re wa, Se l'Oba awon oba.
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Positive
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Adebukola Ogunrinde,
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Negative
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A si fi obinrin na sinu ile Farao.
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Negative
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'It's too late to go there today.' ïåðåâîä íà ðóññêèé ÿçûê è òðàíñêðèïöèÿ
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Negative
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Nigba miiran o ma n wo "
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Positive
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difa fun Marunlelogojo igi oko,
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Positive
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Beena ona imi leleyi la je ko daju..
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Negative
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OS MJI O gbo koran koran Babalawo agbe lo d'ifa fun agbe Eyi ti yoo ma fi oran gbogbo je ho-ho Won ni ko kara nile, ebo ni ko s Mo je, ho-ho ki ngo; ho ho Iworo isope, e wa ba ni lajase ogun Ajasegun laa ba ni lese orisa
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Negative
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See n mi sa ojee (Ibadan ijinle).
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Positive
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Ibinu oro ti baba naa so ni won ni Iyabo ba pada sile yii, bee lo seleri fun toko-tiyawo naa pe oun setan lati fina si gbogbo dukia won, ati pe ihooho ni won yoo ba jade kuro nibe.
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Negative
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Opolongo bi eyo umbo opolongo baba nishe omo niye oniye oun babalawo
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Positive
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opolongo bi eyo umbo opolongo baba nishe omo niye oniye oun babalawo
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Positive
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Aaaah je suis rassuré !
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Positive
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atijouru. ti uurji to-morrow.
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Negative
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"A wa si Allah ati fun u a yio pada."
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Positive
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Ni ipo yii, Emi ko ni idunnu.
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Positive
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"O, ibojì yìí àti òkúta tí mo ti gb between láàárín èmi àti youyin,
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Positive
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Nibi wan sowipe eni to keeko, Ko kin sukun fun eni to wa laaye tabi eni toti ku. (segbe:) E yo wan kuro niwaju.
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Positive
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Enia ko ni agbara,
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Positive
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Kini idinku fun agbegbe ibi isinmi?
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Positive
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Ibeere: "Se o ti ni iye ainipekun?"
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Positive
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E ri mi pe mo kere le fi yan mi je, Ifa inu mi ko Kere,
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Positive
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Mu dinari kan fun mi wá, kí n lè rí i. "
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Negative
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ol lu ni nit,
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Positive
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Fun iná ti a ti ràn ninu ibinu mi; o yoo sun lori nyin. "
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Positive
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si! lo amo! jeje
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Negative
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Ati eniti o ti yipada, ki yoo pada wa?
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Negative
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Aw?n ?na ti o ba ?sin Islam mu fun Is? ?l?hun ati Aabo R?By Abdur Rahman Muhammadul Awwal
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Negative
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Bo jo ro, iwo ni ma balo,
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Positive
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wò ó, kí o sì rí ìtìjú wa.
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Negative
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Ama Jarn la wo dayge age gà.
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Negative
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Ala ti je topic.
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Positive
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Akoko ti Japan nigbagbogbo n yipada.
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Positive
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ti ni guyé rañaa que gué'.
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Positive
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Bí o l'ówó bí o kò ní 'wà 'nkó,
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Negative
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E ku gbogbo igba mi o, Doctor.
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Positive
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Ko si esin teeyan n se laye yi ti Olorun ko gbo adura e.
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Negative
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Ewebe tutu ati saladi adalu, ale fun meji
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Positive
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Hummmm oro po ninu iwe kobo.God knows d best.
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Positive
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Nitori eyi, Oluwa le dariji ese wa ati fun ileri iye ainipekun ni paradise.
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Positive
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Arabinrin wa fun wa ni okuta marun tabi ...
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Positive
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Jot thaki jone jogi nipaayaa,
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Positive
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"Kan ik je joinen?"
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Negative
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Emi o pe lori Oluwa mi.
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Positive
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A pada wa ni gbogbo igba ti a ba wa ni Omaha Area.
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Positive
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êàêèå óñëîâèÿ òðóäà ó âàñ íà ðàáîòå;
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Positive
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Ki B'Aladura titun, ni ti Baba wa yan, O ti l sd Baba wa Tunlase At'ewe m lrun; Dagba sinu Iml, Eniyan gbagbe sugbn lrun niran.
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Positive
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A dupe, a sin a Olorun ti o mo ohun gbogbo.
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Positive
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Adia funAkinoro ti se omokunrin onko,
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Positive
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to jara sidai aakar jaliye,
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Positive
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reveler ni le jour ni Iheure.
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Positive
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Ni ojo ti o sunkun pe ohun ni ibudo,
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Positive
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Ma jeko ya e lenu ti ba lo ra beamer, Able God lasan legbo te lo n sina
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Positive
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Min ba dɛnkɛninya n ma, wo tigi ti to pinpi rɔ.
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Negative
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Aasman Chukar Aa Gaye Bhi Agar,
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Positive
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Awon eranko gan, o fe ku. pelu agbara lon fi ku pa wan. ìpànìyàn leleyi.
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Negative
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"oluo popo eye nile, oluopopo aba obo ekan nile odura oluo popo."
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Positive
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Oli, je to ona
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Positive
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Ya Miyaji Ki Aarti pratidin,
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Positive
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Lamento lo de tú messenger, ojalá lo recuperes.
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Negative
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Adogan kekere gbe ko ko nla ru,
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Positive
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Ma lo fi yan mi kere, kere
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Positive
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By Falope Ibukun
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Positive
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Satan is under my feet ko je lo so ewe agbeje mowo.
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Negative
|
un wuwo bi erin,
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Positive
|
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Yoruba Sentiment Corpus
Dataset Description
This dataset contains sentiment-labeled text data in Yoruba 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: 180,921
- Positive sentiment: 95181 (52.6%)
- Negative sentiment: 85740 (47.4%)
Dataset Structure
Data Fields
- Text Column: Contains the original text in Yoruba
- 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/yoruba-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 Yoruba
- Cross-lingual sentiment analysis research
- African language NLP model development
Citation
If you use this dataset in your research, please cite:
@dataset{yoruba_sentiments_corpus,
title={Yoruba Sentiment Corpus},
author={Mich-Seth Owusu},
year={2025},
url={https://huggingface.co/datasets/michsethowusu/yoruba-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
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Size of downloaded dataset files:
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Size of the auto-converted Parquet files:
6.5 MB
Number of rows:
180,921