Africa Sentiment Datasets
Collection
The collection contains sentiment-labeled text data for 42 African languages
•
43 items
•
Updated
Dataset Viewer
Ewe
stringlengths 9
435
| sentiment
stringclasses 2
values |
|---|---|
Nya la do tso nye nu me le dzɔdzɔenyenye me,
|
Negative
|
Wò fetu asɔ gbɔ ŋutɔ."
|
Positive
|
"Ame kae nye nunyala kple nugɔmesela le mia dome?
|
Positive
|
Alo hafi nàwɔ xexea kple anyigbaa la,
|
Positive
|
Wo Hamesha Tere Pas Ho,
|
Negative
|
na apostolo siwo wòtia to Gbɔgbɔ Kɔkɔe la me vɔ megbe ŋu.
|
Positive
|
Eye Elisa biae be: "Gehazi, afi kae nètso?"
|
Negative
|
Míele ko abe ame kukuwo ene le ame kakowo dome.
|
Negative
|
Mi Afetɔ subɔlawo, mikafui,
|
Positive
|
Nu kae mate ŋu awɔ ame siawo alo wo vi siwo wodzi la egbea?
|
Negative
|
Ke aleke awɔ ne woawu ŋɔŋlɔawo nu mahã?
|
Negative
|
Oo, mi Afetɔ subɔlawo, mikafui,
|
Positive
|
Ne ènye ame dzɔdzɔe la, nuka tsɔm nèle nɛ?
|
Negative
|
ye be believers.
|
Positive
|
Eye mabla nu mavɔ kpli mi,
|
Positive
|
Nye subɔviwo awɔ dɔ kple wò subɔviwo,
|
Positive
|
Esiae anye dzesi na mí."
|
Positive
|
Nenemae míele Afetɔ, mía Mawu la sinu kpɔmee,
|
Positive
|
elabena ame si si nu le la, eyae woagana nui, eye ame si si nu mele o la, woaxɔ esi
|
Positive
|
Lɔɔ cheleŋ, Leya yeema pɛ suɛi o finya ndɔ lo, o nua ndu hɔlla tom tom, ɔɔ mbo poonyial ndu yauwo a bahawɛi ndɔɔ okɔɔ.
|
Positive
|
Mawu axɔ nɛ kaba le fɔŋli.
|
Positive
|
Enugbe mo needi owo, edakun e shanu aiye mi ooo, enugbeeee mo needi owo
|
Positive
|
Vidzidɔ me kutsetse nye fetu tso egbɔ.
|
Positive
|
Eye wotsɔ dɔgbedenyawo vɛ na wo kple ha blibo la katã hetsɔ anyigba la dzi kutsetsewo fia wo.
|
Positive
|
Ke Mawu gblɔ nɛ be: 'Movitɔ, zã sia me ke woabia wò agbe le asiwò me.
|
Negative
|
Mboro wo na, na ndanlafɔ, pan ma ye laga ma naŋgɔ kɔlɔgɔ ki ni,
|
Negative
|
Esi wòwɔ ŋunyɔnu siawo katã ta la, aku kokoko.
|
Negative
|
Ame fafawo asee, eye dzi adzɔ wo.
|
Positive
|
sia age adze la, agba gudugudu."
|
Negative
|
Eye ame siwo xa wain la anoe le nye xɔxɔnu kɔkɔewo."
|
Positive
|
Ame siwo sa vɔ tsɔ bla nu kplim."
|
Positive
|
Wogblɔ na wo nɔewo be:
|
Positive
|
Abraham gblɔ nɛ bena: Kpɔ nyuie, bena nagagbugbɔ vinye la ayi afimae o!
|
Positive
|
Nye subɔlawo akpɔ dzidzɔ, ke miawo la, ŋu akpe mi.
|
Negative
|
Mawu, wò si ko nye nunyala, wò, si ko nyo,
|
Positive
|
'Mia Fofo Nye Nublanuikpɔla'
|
Positive
|
Wo Keh Kr Gayi Thi Ki Laut Kr Aaoon Gyi,
|
Positive
|
E da Mawu nane mi; wa buɔ lɛ.
|
Positive
|
Mawu, kɔ wò asi dzi, eye megaŋlɔ hiãtɔ be o!
|
Positive
|
Amesiwo le ku dzɔm, ke meva o, eye wole ŋu tsom nɛ wu kesinɔnuwo;
|
Negative
|
Ameka wɔ nusiawo?"
|
Negative
|
Elabena Afetɔ gbe wo."
|
Negative
|
Alo fiaa sidzedzee,
|
Positive
|
afi siae mía tɔgbuiwo subɔe le?"
|
Negative
|
Katã ava Fofoa gbɔ,
|
Negative
|
Bulke Wo To Khud Paeda Kye Gae Hain,
|
Negative
|
Eye ame dɔdɔawo trɔ va gblɔe na fia la.
|
Positive
|
Míebia gbe nufiala ene siwo tso New York City be nukae wobuna be wonye kuxi gãwo.
|
Negative
|
Eya ta mana dzo nado tso mewò ne wòafiã wò.
|
Negative
|
Woti Wo Yome Le Dzɔdzɔenyenye ta
|
Negative
|
Nyemazu yomemɔfiala o."
|
Positive
|
Yesu gblɔ be: "Mi katã la nɔviwo mienye."
|
Positive
|
Mose ŋlɔ bena: "Oo Yehowa, . . . hafi towo nava dzɔ, alo hafi nàwɔ xexea kple anyigbaa la, wòe nye Mawu tso mavɔ me yi mavɔ me."
|
Positive
|
"Ame Kae Nye Nunyala Kple Nugɔmesela Le Mia Dome?"
|
Positive
|
Ame sia ame si tia mi la, ŋunyɔnu wònye.
|
Negative
|
Nyiile me mɔ de n' sɔɔ mɔ gyi."
|
Positive
|
Mana viviti si le wo ŋgɔ la nazu kekeli,
|
Positive
|
Nyanyui sia gblɔm míele na mi; ŋugbe si Mawu do na mía fofowo,
|
Positive
|
Ke nye la mele mia si me, miwɔm abe alesi dze, eye wònyo mia ŋu ene.
|
Positive
|
Ke nɔnɔme ka tututu mee ame kukuwo le?
|
Negative
|
Mawu nye amenuvela alegbegbe.
|
Positive
|
Ekema nu ka tae miawoe anye mlɔetɔ akplɔ fia la agbɔe?'
|
Negative
|
Eye wògblɔ be: "Nye, viwò, wò ŋgɔgbevi Esau ye."
|
Positive
|
Eye bometsila anye subɔla na ame si si dzi nyanu le.
|
Negative
|
la, Mawu le eya amea me eye eya hã le Mawu me.
|
Positive
|
Eye makafui le amehawo dome.
|
Positive
|
Le anyigbadzinuwɔwɔwo katã dome la, amegbetɔwo le etɔxɛe.
|
Positive
|
Egblɔ be: "Abe alesi Fofonye fiam ene la, nu mawo ke megblɔna."
|
Positive
|
Ekema nu ka ŋuti miele naneke wɔm le fia la kpɔkplɔ gbɔe ŋu o?"
|
Negative
|
wosubɔa eya ame si nɔa agbe tegbetegbe.
|
Positive
|
Eye eya zu nye xɔnametɔ."
|
Positive
|
Ke esiae nye nya si wogblɔ na mi.
|
Positive
|
Eye wòdaa gbe le wò dɔlélewo katã ŋu;
|
Positive
|
Ku kawoe Mawu di be alɔawo natse?
|
Positive
|
Afi nèle ŋeŋem le game,
|
Positive
|
Ne Mawu mekpɔ dzinye o,
|
Negative
|
Eye nye fetu le nye Mawu gbɔ."
|
Positive
|
Miate ŋu ade ta agu le afi sia.'
|
Positive
|
Ne wotrɔ dzime la etsɔnɛ kea wo.
|
Positive
|
Ka asi towo ŋu, ne woatu dzudzɔ.
|
Positive
|
Wobe wowɔa funyafunya amewo le dzo mavɔ me tegbee.
|
Negative
|
Si Mawu fia wò.
|
Positive
|
Azu wo tɔ tegbee;
|
Positive
|
Elabena wogblɔ be: "Makpɔ ale si wòava nɔ na mí mlɔeba o."
|
Negative
|
To tsitretsitsia dzi la, anya wɔ be wòava nɔ agbe tegbee le anyigba dzi.
|
Positive
|
Nya dodzidzɔname ka gbegbee nye esi wose!
|
Negative
|
Etu nye nubabla la."
|
Positive
|
Azɔ Yesu gblɔ be: "Menye Mose ye tsɔ Se la na mi oa?
|
Negative
|
Eya hã agbe nu le mia gbɔ.
|
Negative
|
"Esi wò dzi de asi dada me, eye nèle gbɔgblɔm be, 'Nye la, mawu menye.
|
Positive
|
Eya ta wogblɔ be: "Baba na mí, elabena nu sia tɔgbi medzɔ kpɔ o!
|
Negative
|
Woafɔ kukuawo dometɔ akpa gãtɔ va anyigba dzi
|
Positive
|
Amesiwo axɔ edzi ase la anɔ agbe tegbee le anyigba dzi.
|
Positive
|
Gbɔwòe nye kafukafuha tso le ameha gãwo dome.
|
Positive
|
Nenemae mawɔ le nye subɔlawo ta;
|
Negative
|
be ever denied?'
|
Negative
|
Menye ŋkutsalawoe wò dɔlawo nye o."
|
Positive
|
Esi Farao va se nu tso eŋu la, edi be yeawu Mose.
|
Negative
|
Ke azɔ ne menyo ŋuwò o la, ekema magbugbɔ."
|
Negative
|
Woate ŋu azã lãwo azɔ.
|
Negative
|
End of preview. Expand
in Data Studio
Ewe Sentiment Corpus
Dataset Description
This dataset contains sentiment-labeled text data in Ewe 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: 337,488
- Positive sentiment: 196712 (58.3%)
- Negative sentiment: 140776 (41.7%)
Dataset Structure
Data Fields
- Text Column: Contains the original text in Ewe
- 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/ewe-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 Ewe
- Cross-lingual sentiment analysis research
- African language NLP model development
Citation
If you use this dataset in your research, please cite:
@dataset{ewe_sentiments_corpus,
title={Ewe Sentiment Corpus},
author={Mich-Seth Owusu},
year={2025},
url={https://huggingface.co/datasets/michsethowusu/ewe-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
- 9
Size of downloaded dataset files:
8.21 MB
Size of the auto-converted Parquet files:
8.21 MB
Number of rows:
337,488