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
Lingala
stringlengths 1
484
| sentiment
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428k
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|---|---|---|
Bongo atunaki bango: 'Mpo na nini botelemi awa mokolo mobimba mpe bozali kosala eloko te?
|
Negative
| 0 |
Nalobi epai ya bino ete, iyo; nzokande bokoli te o boyebi boko bobongo nie.
|
Negative
| 1 |
Mpe soki mokomoko azali na mokumba, akomona ete losambo na kati ya libota etaleli mpe ye.
|
Positive
| 2 |
Mpe tala, lisusu, balobaki eye etindamaki bango na Nkolo; yango wana, mazali ma sembo mpe ma solo.
|
Positive
| 3 |
Pamba te, bakoyoka kaka ete osi'okomi awa!
|
Positive
| 4 |
Mityelá mokano ya kozwa eloko oyo ezali na litomba mingi koleka bozwi ná biloko ya kobikela.
|
Positive
| 5 |
Atako mana ezalaki likabo oyo eutaki epai ya Nzambe, epesaki bato bomoi ya seko te.
|
Negative
| 6 |
Nakotya yo obatela biloko mingi."
|
Positive
| 7 |
Ndenge nini toyebi ete Nzambe andimaka te ndenge nyonso ya kosambela ye?
|
Negative
| 8 |
Tala, nkoma izali liboso lya bino; soko bokokamola yango ekozala mpo ya bobebisami bwa bino moko.
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Positive
| 9 |
Banda vi banaya bayimaan hai loko...
|
Positive
| 10 |
Mpe akopika bahema na ye oyo ezali lokola bandako minene kati na mbu monene mpe ngomba mosantu ya Kitoko; mpe akoya tii na nsuka na ye, mpe akozala na mosungi te."
|
Negative
| 11 |
Olingi koyeba makambo mosusu etali Bokonzi ya Nzambe mpe oyo ekosala?
|
Negative
| 12 |
Kasi ateyaki mpe bango bábondelaka ete Bokonzi ya Nzambe eya mpe bázelaka ntango yango na motema esengo.
|
Positive
| 13 |
Na ndakisa, Biblia esaleli liloba lobɔkɔ mbala ebele.
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Positive
| 14 |
Na kozela banzelu bazongaki mpe na boboto batunaki ye, "Mwasi, ntina nini ozali kolele?
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Negative
| 15 |
Yango ekosalisa yo oyeba oyo Yehova azali kosɛnga yo mpe ndenge oyo asalisaki basaleli na ye na kala.
|
Positive
| 16 |
Pamba te apesaki motindo mpe yango ekelamaki.
|
Positive
| 17 |
Moyengebene akimaka mpo na kokɔta kuna mpe azwaka libateli."
|
Positive
| 18 |
Litomba oyo okoki kozwa: Nzambe alaki ete soki oyebi ye mpenza malamu, okozwa bomoi ya seko.
|
Positive
| 19 |
Na yango, tokomonisa bwanya soki tosaleli makoki na biso ya kokanisa mpe tobakisi boyebi na biso ya Liloba ya Nzambe.
|
Positive
| 20 |
Mpo soko ezali moko o ntei ya bino oyo asali bolamu, akosala na nguya mpe makabo ma Nzambe.
|
Positive
| 21 |
Okoki kopusana penepene na Nzambe kaka soki otyeli ye motema, mpe soki ondimeli ye.
|
Positive
| 22 |
Natatoli lisusu ete tokoki te kokumbama libanda soki tokolanda toli ya profeta ya Nzambe.
|
Positive
| 23 |
Ntango "mokolo ya kosambisama" ya Nzambe ekoya, baoyo baponi kozala banguna ya Nzambe bakobebisama ndenge wana.
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Negative
| 24 |
Eyebisaka bango ete bazali bana ya Nzambe mpe ete basengeli kolya limpa mpe komɛla vinyo
|
Positive
| 25 |
Kasi, elimboli ete baoyo bakumisaka mpenza nkombo ya Nzambe bakoki kobelela ye ata na ngonga nini mpo na kozwa libateli.
|
Negative
| 26 |
Nzambe atalelaki yango na ndenge ya malamu mpo asala ndenge asali na mokolo ya lelo: kobatela bato mingi na bomoi."
|
Negative
| 27 |
Soki moto moko nde asalá Nzambe, moto yango asengeli kozala Mozalisi.
|
Negative
| 28 |
Boye okotambola na kimya na nzela na yo, mpe ata lokolo na yo ekotutana na eloko moko te."
|
Positive
| 29 |
To kofandisa bango na se ya mayi ti ba kokufa kuna.
|
Positive
| 30 |
Ndenge nini toyebi ete bato nyonso oyo bazwaki elimo ya Nzambe baponamaki te mpo na kokende likoló?
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Negative
| 31 |
Na nsima mposa wana, ntango ezwi zemi, eboti lisumu."
|
Negative
| 32 |
Ye Oyo Aleki Likolo azali na boyebi?"
|
Positive
| 33 |
mpe bakopesa ye kombo Emanuele;
|
Positive
| 34 |
Na nsima mposa wana, ntango ekoli, eboti lisumu."
|
Negative
| 35 |
Na Nzambe azali moyebi wa eloko inso ."
|
Positive
| 36 |
le lon ponana ye paroranga ki,
|
Negative
| 37 |
Sima na yango, bakobima na mokili yango mpe bakosambela ngai na esika oyo."
|
Positive
| 38 |
Ntango azalaki awa na mabele, atikalaki sembo tii na liwa.
|
Positive
| 39 |
Mpo na nini Nzambe abundelaki Bayuda te ndenge asalaki yango kala?
|
Negative
| 40 |
Tala, nalobi epai ya bino, ete ezali o ngambo yoko lokola ezali o esusu; mpe ekozala epai ya moto engebene na mosala mwa ye.
|
Positive
| 41 |
Emonani na misala na bango ete babosanaki te libula na bango, to makambo oyo bateyaki bango.
|
Positive
| 42 |
Moto akokana, nzambe akosukïsa (feat.
|
Positive
| 43 |
Moize amonisaki bolingo mpo na Nzambe mpe mpo na baninga na ye Bayisraele.
|
Positive
| 44 |
Elinga Nzambe ete ekoka kozala o mikolo mya ngai; kasi yango ezala mosika te to mosika, o yango nakosepela.
|
Positive
| 45 |
le titakrai ye mai san,
|
Positive
| 46 |
Bokanisi batongi yango na mayi esika bato ya mboka bakokoka kokende te pamba?
|
Negative
| 47 |
Andimaka moto nyonso oyo alingi kosambela ye.'
|
Positive
| 48 |
O bandimi! tango nini bokososola?
|
Positive
| 49 |
Na yango, atikelá basaleli ya Nzambe lelo oyo ndakisa moko malamu.
|
Positive
| 50 |
Mpo na sikoyo, ata baoyo basalaka nyonso mpo na kosepelisa Nzambe bakutanaka na mitungisi.
|
Negative
| 51 |
Maze Bakoseli Ngai Makambo Mpo Nakosa Na Wele,
|
Negative
| 52 |
Ndako nyonso oyo bakokuta mopɛngwi, esengelaki kobebisama."
|
Negative
| 53 |
Azalaki koloba na basaleli na ye na boboto, mpe na ndenge oyo ebongi mpenza.
|
Positive
| 54 |
Pamba te bato ya masumu mpe basalaka bongo.
|
Negative
| 55 |
Boye, bakosala makambo na bwanya ata soki ozali te.
|
Positive
| 56 |
Na yango, "Goge" oyo mokanda ya Ezekiele to Emoniseli elobeli, ezali Satana te.
|
Negative
| 57 |
Bongo alobaki na ngai: Ezali baoyo bawuti konyokwama mingi penza.
|
Positive
| 58 |
Nini ekosalisa yo ntango ozali kosolola na basusu mpo na Nzambe mpe mpo na bozalisi?
|
Negative
| 59 |
Mibembo mya ye o kati ya esobe, mpe bongo na bongo.
|
Positive
| 60 |
Yakobo akendaki liboso ya libota na ye, mpe afukamaki mbala nsambo liboso ya ndeko na ye.
|
Positive
| 61 |
Batu oyo basili kosala malamu, bakosekwa mpo na kozwa bomoi.
|
Positive
| 62 |
Na nsima, Nzambe 'akopusana penepene na yo.'
|
Positive
| 63 |
Ata bongo, bolinganaka mpe bolingi te kosalana mabe.
|
Positive
| 64 |
Tótalela mpe ndakisa ya Yobo, moto moko ya sembo oyo alobaki: "Nasalá kondimana na miso na ngai.
|
Positive
| 65 |
Mpe nalobi epai ya bino ete babikisamaki.
|
Positive
| 66 |
Bango nde ba ko lamusaka biso, tongo esi etani
|
Positive
| 67 |
Bamosusu balobaki ete: "Liloba oyo ezali makasi; nani akoki koyoka yango?"
|
Negative
| 68 |
Tango nini okopesa etumbu na bato oyo bazali konyokola ngai?
|
Negative
| 69 |
To owanganaki kondima?'
|
Negative
| 70 |
Liloba ya Nzambe ekebisi biso ete: "Bókangana te na ekanganeli ya mabe esika moko na bato oyo bazali bandimi te.
|
Positive
| 71 |
Bongo bokengeleke, zambi boyebi ata mokolo ata ngonga te."
|
Negative
| 72 |
Kasi mpo na baponami, ba oyo ye apona, yango wana atiaki yango mokuse.
|
Negative
| 73 |
Lokola basi ya mibu nyonso, totambolaka kati ya pole na Ye .
|
Positive
| 74 |
Moto nyoso akotosa te, akozwa etumbu ya makasi;
|
Negative
| 75 |
Yebisá bato ete bámeka komata na Ngomba Sinai te.'
|
Negative
| 76 |
Kutu, akebisaki nde bakristo boye: "Bókangana te na ekanganeli ya mabe esika moko na bato oyo bazali bandimi te.
|
Positive
| 77 |
Pamba te, ye awutaki na suka ya mokili mpe ayaki mpo na koyoka bwanya ya Salomo.
|
Positive
| 78 |
Abatelaka basambeli na ye.
|
Positive
| 79 |
Tomonaki bondimi na bango mpe lolenge bazalaki kosalela yango.
|
Positive
| 80 |
Alobaki ete: "Kaka ndenge Tata ateyaki ngai, ndenge mpe nazali koloba."
|
Positive
| 81 |
Nakomonisa bango ete bazali na libunga.'
|
Negative
| 82 |
Nzambe azali na nguya oyo ezangi ndelo mpe azali na mposa ya kosalela yango mpo na bolamu na biso.
|
Positive
| 83 |
Alakaki ete bana ya Yakobo bakokóma ekólo moko ya nguya.
|
Positive
| 84 |
Nzambe na sengi se na yo ooo, bomengo oo bwanya mayele eeee,
|
Negative
| 85 |
Kaka ntango bandeko mosusu bazongaki na ntɔngɔ makasi nde nakutanaki na bango."
|
Positive
| 86 |
Kasi abatelaki kaka Nowa oyo azalaki koteya bosembo, mpe bato sambo mosusu elongo na ye.
|
Negative
| 87 |
Sikoyo, kanisá ete baanzelu bazali koyebisa yo: "Kondima lokuta ya Satana te."
|
Positive
| 88 |
Akomaki boye: "Nani akokoka na mokolo ya koya na ye, mpe nani akotɛlɛma ntango ye akomonana?
|
Negative
| 89 |
Mais bakosambua.
|
Positive
| 90 |
Ye ayebi makambo nyonso!
|
Positive
| 91 |
Kutu, 'asepelaka kolimbisa.' - Nz.
|
Positive
| 92 |
Zuwa na bango etindaki bango básala makambo oyo na nsima, epesaki bango mpasi mingi na motema.
|
Negative
| 93 |
mateya ya solo oyo ateyá yo?
|
Positive
| 94 |
Oyaki kososola ete bato nyonso bazali mosika na Nzambe.
|
Negative
| 95 |
Makomami emonisi mpe ete bamonisaki mpenza botosi oyo esengeli na likambo yango.
|
Positive
| 96 |
ya til des signes ou pas ?
|
Negative
| 97 |
Totunaki bango boye: "Mpo na nini bakristo basambelaka Yesu, ekulusu, Maria, mpe bikeko mosusu nzokande Mibeko Zomi epekisi yango?"
|
Negative
| 98 |
Asalaki mokili wuta na mayi mpe na nzela ya mayi.
|
Positive
| 99 |
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in Data Studio
Lingala Sentiment Corpus
Dataset Description
This dataset contains sentiment-labeled text data in Lingala 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: 427,979
- Positive sentiment: 251923 (58.9%)
- Negative sentiment: 176056 (41.1%)
Dataset Structure
Data Fields
- Text Column: Contains the original text in Lingala
- 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/lingala-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 Lingala
- Cross-lingual sentiment analysis research
- African language NLP model development
Citation
If you use this dataset in your research, please cite:
@dataset{lingala_sentiments_corpus,
title={Lingala Sentiment Corpus},
author={Mich-Seth Owusu},
year={2025},
url={https://huggingface.co/datasets/michsethowusu/lingala-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:
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Number of rows:
427,979