Mossi
stringlengths 10
271
| sentiment
stringclasses 2
values |
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Bãwã idan yã yi salla? | Negative |
"Da zoe rabeem ye, bala, mam bee ne foom. | Positive |
GhaM Ko BadnaaM Kar Gaye Aansu, | Positive |
Nees nkaum yim Dudek ok - | Negative |
Yef Y ne deye, thou gost to helle; | Positive |
Dil me lagi aag na bujh payegi, | Negative |
Lamhon ki ek kitaab hai ye zindagi, | Positive |
Humko kisi kitaab me ye to nhn mila, | Positive |
kau tu yg noob,dah kne delete la kafir | Positive |
qu'il ne false ne ne ploie, | Positive |
mercianþii încearcã sã ne facã sã credem cã ei, | Positive |
tab jaa kar hmne hai ye aajadi paayi , | Positive |
Ne prefãceam cã afarã e soare, | Positive |
Which ye shall taste before ye hang, to mortifie ye; | Positive |
ba, to, bã zã ku aikata ba, sabõda | Negative |
Mai bine sã taci decât sã vorbesti rãu. | Positive |
Me ya'o samebõrõta | Negative |
Lehrã bin ãyã Maiyã khosiyã lotãdiyã | Positive |
ye rooz too jahanam hamdigaro mibinim | Positive |
Les fards à yeux. | Positive |
Ke Adakunom se mak be yir, aky ti daam yir ke a ti ra yir ? | Negative |
Dindimmaa ko a faamaa ye ko, 'M faamaa, n na keetaafengo dii n na, meng mu n niyo ti.' | Positive |
Bãmb maana fãa, baa a ye ka pa ye." | Positive |
Shyad Meri Kasoor ye hai ki aansu me Pani kam hai, | Negative |
Siala bee ne yãmb paama barka n yiid paga fãa, | Positive |
Ye shaairi ye kitaabein ye aayatein dil ki, | Positive |
Bãmb na n tika bãad-rãmb ne b nusi, la b na n paama maagre. | Positive |
Says, Wae be to ye, waefu water, | Positive |
sã stea munţii fãrã grai, | Negative |
Kam ne bar ar ajã Xitumã karõn kum, | Positive |
ye kaam tum karne waali ho, right...??? | Negative |
Moses Ok Nkakra B Y Yie | Positive |
moses ok nkakra b y yie | Positive |
"ai vã mai miraþi cã marea nu vã lasã sã mergeþi! | Positive |
ye jo muhabbat hai, ye unakaa hai kaam - | Positive |
Ba ije markam dja ba me'ã ar amã karõ. | Negative |
Vreau sã mã otie tot satul. | Positive |
La b leoka a Zezi n yeele: Zu-soaba, wa n ges-y-yã. | Positive |
Da ges-y y mens wa yam dãmb ye. | Negative |
Pe ba le yãŋ cã ma yee Yãhã kai- sroŋ, ma ka Nsãn n ga pe tãã yi loho wo. | Positive |
La Israɛll nebã wa n yeela a Moiiz yaa: 'Tõnd kongame. | Negative |
aadmi ne aaine ko hairt me daal diya hai; | Negative |
Mose maa yevese yem ken tar u Midian. | Negative |
Dayã garibi bandagi; samatã shêla karãra, | Positive |
Vã rog sã mã înþelegeþi. | Positive |
T'a Balaam leok yaa: 'Fo yaanda maam. | Negative |
Sã mai cearã o datã. | Positive |
Kon Suhãgan Divã Bãliã Meri Maiyã | Positive |
Maane na maane koyee duniya yeh sari , | Positive |
ye eh?ape yg d usha tu? | Negative |
kyaa error aa raha hai ye bataye. to mai kuchh bata sakata hu. | Positive |
Bãmb b naasa fãa yaa toor-toore." | Positive |
All Die be Die nti, yes nso yentie obiaa dabi ara da, | Positive |
La bõe la d ne a Miise wakatã? | Negative |
choke dee na toog toog kon. | Negative |
N-o sã mã crezi, | Positive |
Bala tõnd yãa bãmb ãdg yaanga, la tõnd waame n na n waoog bãmba. | Positive |
Sabõda makãho yã je masa. | Negative |
hai tujhse ye ummed us maa ki, | Positive |
Khwaab bun ye zara, | Negative |
En kaer Alba neb a vije, | Negative |
Comme la machalï kã supã enfumée, | Negative |
Pm sent to ye both. | Positive |
Pagal hai saala ye, | Positive |
ye samaa, samaa hai ye pyaar kaa - | Positive |
Raam ka naam badnaam na karo, | Positive |
A Zã-Mark ra bee ne bãmb n sõngd-ba. | Positive |
Withã coffeeã whenã youã haveã timeã toã spare. | Positive |
Gom-kãens yɛɛsa bãmba, la b basa a Zezi n looge. | Negative |
Bahu ye to bta tuje ye sab aakhir kisne btaya ha, | Negative |
ã DAN GE R! | Positive |
Haha, blog yaa later. | Negative |
Tõnd sõngda taaba, | Positive |
yesterday y maana. | Negative |
Rehne de ye kitaab tere kaam ki nahi, | Positive |
nikakõixõ a mã ipaoni keskara anã mã ãfe tari kexa ramãkani. | Positive |
Agar ye haal hai dil kaa to koi samjhaaye, | Negative |
A Dieu, dans ma prière, | Positive |
meng zhong de eji uudam - | Positive |
Waseem yaar ye free he to hay.. | Negative |
Koi kya de raaye hamaare baare mai, | Negative |
Bɛɛbã na n digame, | Negative |
Vã rog sã mã iertaþi. | Positive |
ye kyaa kar Daalaa tuune dil teraa ho gayaa - | Negative |
ye to duniya ka dastur h yaaro, | Positive |
tiIe oa yTo) uI B oT - oy opy ye BI- | Negative |
Dil ko hai teri justujoo, yaa nabi, | Positive |
M baaba maana kaalem zabrã poor bilfu. | Negative |
ii se loo dare a mii mamaa y a mii tia.. | Positive |
Acum o sã ne fie greu, o sã ne parã cã nu mai aveti solutii. | Negative |
Kam che kha v ta ye maa la be dua raa, | Positive |
Ka ce, "Shin, to, bã zã ku yi tunãni ba?" | Negative |
Wo ek boond ka Paani hu Mai, | Negative |
Haaye mere paas se hoke, | Positive |
Lot Ao ye mere DIL ki sada hai,, | Positive |
mam tõe gesã ball rar a ye zãng tele wã zugu. | Positive |
Ore ha'e ko tetã ãngapu, | Positive |
B est pour balle be be balle | Negative |
Rasem a naas-n-soabã, bõe la a maan-yã? | Negative |
Dãri Kluãng, sempãt lãgi terbãbãs ke Tãngkãk. | Negative |
Mossi Sentiment Corpus
Dataset Description
This dataset contains sentiment-labeled text data in Mossi 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: 125,695
- Positive sentiment: 74409 (59.2%)
- Negative sentiment: 51286 (40.8%)
Dataset Structure
Data Fields
- Text Column: Contains the original text in Mossi
- 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/mossi-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 Mossi
- Cross-lingual sentiment analysis research
- African language NLP model development
Citation
If you use this dataset in your research, please cite:
@dataset{mossi_sentiments_corpus,
title={Mossi Sentiment Corpus},
author={Mich-Seth Owusu},
year={2025},
url={https://huggingface.co/datasets/michsethowusu/mossi-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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