Datasets:

michsethowusu
/

dyula-sentiments-corpus

Dyula stringlengths 10 281	sentiment stringclasses 2 values
Aw murutira ka tɛmɛ aw lamini siya nunu kan.	Negative
Nga min sɔrɔla dɔɔni dɔɔni,	Negative
I ka kuma ye fitinɛ ye ne sen ye.	Positive
A hakili b'a la ko an ye buguri ye.	Negative
a ye sankolo kɛ a ka hakilitigiya la.	Positive
Jamana halakira u kɔfɛ, fɔɔ mɔgɔ te bɔ yen, mɔgɔ te tɛmɛ yen.	Negative
Ne bolo barikaman sababu la, a yɛrɛ bena u gwɛn ka bɔ a ka jamana kɔnɔ."	Positive
Olu dɔrɔn tun bena kisi.	Negative
Ale be koo bɛɛ lɔn.	Positive
O suu nin na, a ma dumuni kɛ, a m'a to a ka gɛrɛfɛmusow si ka na la a kɔrɔ, a ma se ka sinɔgɔ.	Negative
O la, kabini sisan i bena kɛlɛ sɔrɔ."	Negative
A y'u bɔsi u juguw bolo loon min na,	Positive
Dugutigi b'a fɔ ko: 'Hɔnhɔn, ko: su ka don.'	Negative
ne bena n kɔɔ le sin u ma u bɔnɛ loon na."	Positive
nga u dusu yɔrɔ ka jan ne la.	Negative
O ye nations !	Positive
An tora an ka kɔlɔsili kɛyɔrɔw la,	Positive
a b'u tanga kojugu ma janko u kana ben.	Positive
"An kɛra nafolotigiw ye,	Positive
u ye kojugu caaman minw kɛ,	Positive
o tuma na, e bi gèlèya ni ka se ne ma an ka so,	Positive
Ala le y'an dogoyɔrɔ ye.	Negative
Loon min na mɔgɔ b'a yɛrɛ majigi,	Negative
Que yo ya lo saba todo,	Negative
Nga an yo mannin be'n, an yo mannin min."	Positive
Ala ya wula nɔgɔya. .	Negative
Muso fanan ma a fɔ ko ale kɔrɔcɛ le wa?	Negative
Adamadenw bɛɛ bɔra u mɔgɔ fila nunu na.	Positive
Mɔgɔ minw be Ala kanu ani u be mɛnni kɛ a fɛ, olu lo bena dugukolo fa.	Positive
O tigi ye hakɛ yafabali kɛ."	Positive
o la, a yɛlɛmana ka kɛ u jugu ye, a y'u kɛlɛ.	Negative
"Foyi tun te an faaw fɛ fɔɔ batofɛnkolon dɔrɔn,	Positive
n bena u jɛni kɛlɛ loon na, mankanba kɔnɔ,	Positive
Ne tɔgɔ lara soo min kan, u y'o ka joow bila o kɔnɔ, k'o nɔgɔ.	Negative
Nuhun tun ye mɔgɔtilennin ye, a jalakibali tun lo a ka waati mɔgɔw cɛma.	Positive
Kuma kelen fɔ dɔrɔn, ne ka baaraden bena kɛnɛya.	Positive
A man fisa an ka segi ka taga Ezipiti wa?"	Negative
An dɔ, "I-a koe min ma ka, nn ma a ɔ sɔn ni a gbasaya chɛ ɛ wan i boo ɔ, a ma koe a.	Negative
Mi sila ki yo ma kan ma yo maga kanla fanla le?"	Negative
Nga aw bena halaki pewu!	Negative
U bena i dɛmɛ ka mɔgɔ nunu ka doni ta, janko i kana o ta i kelen.	Negative
Mɛn dooman, karo kɔnin, a ka wo lasii su kun na.	Negative
U bena i wele ko Masaba ka dugu,	Positive
I ra n gbɛn ka bɔ duu kan bi.	Positive
ma yɛn tagawa ni wa ki kagala ke ni.	Positive
A ka kalandenw tagara dumuni sanyɔrɔ dugu kɔnɔ.	Negative
Ne be u di e n'i dencɛw ma ka kɛ aw niyɔrɔ ye tuma bɛɛ.	Positive
Wasabaliya dogolen tun tè an na fana, Ala ye o seere ye.	Positive
Yala suuw be ni jigiya ye wa?	Negative
k'a kuun biri duguma i ko biin,	Positive
Sukununi nata bena kɛ o cogo kelen na.	Negative
Nkili nkili ka we kili ododo	Positive
Ni o cè ye ko jugu kè, u ka a sendon."	Negative
Delili ye an ka batoli faan dɔ ye.	Positive
Ne bena n ka sagaw kisi ka bɔ aw daa la, u tena kɛ aw ka dumuni ye tugu."	Negative
O soon nin bena aw ka tigɛgwɛlɛya yira, a bena aw halaki i n'a fɔ tasuma.	Positive
Aw te faamuli kɛ halibi wa?	Negative
U ye dugu barikamanw halaki,	Positive
Yafali - N ben'a sɔrɔ cogo juman?	Negative
Ka "segi ka wolo tugu," o kɔrɔ ko di?	Positive
Nka Musa y'a fɔ ko: 'Ne tɛ foyi ye.	Negative
O ka fisa ni dencɛ ni denmuso sɔrɔko ye.	Positive
Fɛɛn bɛɛ kuntigi be se k'o lɔn wa?"	Positive
Se tɛ ne ye k'a dilan, se tɛ dugu mɔgɔ wɛrɛ ye k'a dilan, o dun bɛna kɛ cogo di ?	Negative
An de b'a kalifa i ma, a ka sigi hɛra la, a ka wuli hɛra la.	Positive
Ne tun ye min di olu ni u faaw ma."	Positive
a ye nɛɛ ko piin?	Negative
i ka baara kɛ tere kururu wa ?	Negative
E k'i jija o la, n'o kɛra, i bena i yɛrɛ kisi ani k'i lamɛnbagaw fana kisi.	Positive
Mun na aw b'a fɛ dugu nin ka kɛ tomo ye?	Negative
hakilitigiya be sɔrɔ sitigi fɛ.	Positive
N'a sɔrɔ Masaba bena fara ne kan, ne bena se k'u gwɛn i ko a tun y'a fɔ cogo min na."	Positive
Ala y'a ye ko fɛɛn dɔ tɛ yen nankɔtu nin kɔnɔ.	Negative
A y'a yira ko adamaden dafalen, see dira min ma ka koow latigɛ a yɛrɛ ma, a be se ka kantigiya dafalen kɛ Ala ye hali ni Sutana ye koo o koo la a kan.	Negative
Mɔgɔjugu nunu ye koo min la ne kan, ne bena sa o kama, k'a sɔrɔ ne m'o kɛ."	Positive
asobi ni iko yo -	Positive
O ye sariya ye min tena dabila abada u n'u kɔmɔgɔw bɛɛ fɛ.	Positive
Bi, mɔgɔ caaman tɛ mɛnni kɛ Ala fɛ.	Negative
Nga sisan n deen, i ka dumuni kɛ ka minni kɛ, Matigi bena i dɛmɛ."	Positive
Taga hɛrɛ la, i kɛnɛyanin ka to."	Positive
A ko: "Masaba, e y'i ka jama min bɔ Ezipiti n'i yɛrɛ ka sebagaya n'i ka fanga ye, mun na i be dimi u kɔrɔ ten?	Negative
ne ka mɔgɔw, aw ye tulo malɔ ne fɛ.	Positive
Walima i y'o mɛn mɔgɔ dɔw le fɛ?"	Positive
n te segi kɔ fana."	Negative
U n'u faaw murutira ne ma fɔɔ ka na se bii ma.	Negative
be mad? lo realii?	Positive
"Damasi tena kɛ dugu ye tugu,	Negative
YALA i ma deli ka dajuru dɔ ta ani k'a ye kɔfɛ ko a ka gwɛlɛ k'a dafa wa?	Negative
i y'a fɔ ko n kana siran!	Positive
Miiri k'a filɛ o bena min kɛ i la.	Positive
Aw ye taga tasuma don a la."	Negative
e ka baarakɛlaw ka dalili lamɛn.	Positive
U bena soow lɔ, nga u tena sigi u kɔnɔ,	Negative
"Mi ma mi ye ni fuun kɛ ma yiri shyɛn ye wɔ le?	Negative
Lazari tun tɛ sankolo la, a tun tɛ jahanama tasumaman fana kɔnɔ.	Negative
O tuma na, i bena mun le kɛ i tɔgɔba nin kosɔn?"	Positive
Matigi be se k'o kɛ teliman na!	Positive
aw y'o kɛ jinaw ye k'aw Danbaga darabɔ.	Negative
A kɛra yɔrɔlakolon ye, mɔgɔ te yen, i n'a fɔ a be cogo min na bii.	Positive
An bena koo caaman kalan Dawuda koo la.	Positive

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Dyula Sentiment Corpus

Dataset Description

This dataset contains sentiment-labeled text data in Dyula 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: 36,382
Positive sentiment: 20884 (57.4%)
Negative sentiment: 15498 (42.6%)

Dataset Structure

Data Fields

Text Column: Contains the original text in Dyula
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/dyula-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 Dyula
Cross-lingual sentiment analysis research
African language NLP model development

Citation

If you use this dataset in your research, please cite:

@dataset{dyula_sentiments_corpus,
  title={Dyula Sentiment Corpus},
  author={Mich-Seth Owusu},
  year={2025},
  url={https://huggingface.co/datasets/michsethowusu/dyula-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: 0

Size of downloaded dataset files:

1.2 MB

Size of the auto-converted Parquet files:

1.2 MB

Number of rows:

36,382

Collection including michsethowusu/dyula-sentiments-corpus

Africa Sentiment Datasets

Collection

The collection contains sentiment-labeled text data for 42 African languages • 43 items • Updated 2 days ago