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
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 |
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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
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Size of downloaded dataset files:
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Number of rows:
337,488