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
stringclasses 2
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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
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Atako mana ezalaki likabo oyo eutaki epai ya Nzambe, epesaki bato bomoi ya seko te.
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Negative
| 6
|
Nakotya yo obatela biloko mingi."
|
Positive
| 7
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Ndenge nini toyebi ete Nzambe andimaka te ndenge nyonso ya kosambela ye?
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Negative
| 8
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Tala, nkoma izali liboso lya bino; soko bokokamola yango ekozala mpo ya bobebisami bwa bino moko.
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Positive
| 9
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Banda vi banaya bayimaan hai loko...
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Positive
| 10
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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
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Olingi koyeba makambo mosusu etali Bokonzi ya Nzambe mpe oyo ekosala?
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Negative
| 12
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Kasi ateyaki mpe bango bábondelaka ete Bokonzi ya Nzambe eya mpe bázelaka ntango yango na motema esengo.
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Positive
| 13
|
Na ndakisa, Biblia esaleli liloba lobɔkɔ mbala ebele.
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Positive
| 14
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Na kozela banzelu bazongaki mpe na boboto batunaki ye, "Mwasi, ntina nini ozali kolele?
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Negative
| 15
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Yango ekosalisa yo oyeba oyo Yehova azali kosɛnga yo mpe ndenge oyo asalisaki basaleli na ye na kala.
|
Positive
| 16
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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
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Na yango, tokomonisa bwanya soki tosaleli makoki na biso ya kokanisa mpe tobakisi boyebi na biso ya Liloba ya Nzambe.
|
Positive
| 20
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Mpo soko ezali moko o ntei ya bino oyo asali bolamu, akosala na nguya mpe makabo ma Nzambe.
|
Positive
| 21
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Okoki kopusana penepene na Nzambe kaka soki otyeli ye motema, mpe soki ondimeli ye.
|
Positive
| 22
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Natatoli lisusu ete tokoki te kokumbama libanda soki tokolanda toli ya profeta ya Nzambe.
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Positive
| 23
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Ntango "mokolo ya kosambisama" ya Nzambe ekoya, baoyo baponi kozala banguna ya Nzambe bakobebisama ndenge wana.
|
Negative
| 24
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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
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Soki moto moko nde asalá Nzambe, moto yango asengeli kozala Mozalisi.
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Negative
| 28
|
Boye okotambola na kimya na nzela na yo, mpe ata lokolo na yo ekotutana na eloko moko te."
|
Positive
| 29
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To kofandisa bango na se ya mayi ti ba kokufa kuna.
|
Positive
| 30
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Ndenge nini toyebi ete bato nyonso oyo bazwaki elimo ya Nzambe baponamaki te mpo na kokende likoló?
|
Negative
| 31
|
Na nsima mposa wana, ntango ezwi zemi, eboti lisumu."
|
Negative
| 32
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Ye Oyo Aleki Likolo azali na boyebi?"
|
Positive
| 33
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mpe bakopesa ye kombo Emanuele;
|
Positive
| 34
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Na nsima mposa wana, ntango ekoli, eboti lisumu."
|
Negative
| 35
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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
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Ntango azalaki awa na mabele, atikalaki sembo tii na liwa.
|
Positive
| 39
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Mpo na nini Nzambe abundelaki Bayuda te ndenge asalaki yango kala?
|
Negative
| 40
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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
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Moto akokana, nzambe akosukïsa (feat.
|
Positive
| 43
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Moize amonisaki bolingo mpo na Nzambe mpe mpo na baninga na ye Bayisraele.
|
Positive
| 44
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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
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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
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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
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Maze Bakoseli Ngai Makambo Mpo Nakosa Na Wele,
|
Negative
| 52
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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.
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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
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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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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:
17.7 MB
Size of the auto-converted Parquet files:
17.7 MB
Number of rows:
427,979