Swahili Stopwords
Description
A Swahili stop-words dataset is a curated collection of function words that carry minimal semantic weight and are commonly omitted during text preprocessing in natural language processing (NLP) workflows. These words, while integral to syntactic structure, can be excluded without compromising the overall semantic integrity of textual data. The availability of such a dataset is critical for optimizing NLP tasks, including text classification, sentiment analysis, and information retrieval, as the removal of stop-words reduces dimensionality and computational complexity, thereby enhancing algorithmic efficiency and model performance. Characteristics of Stop-Words: - High Frequency: Stop-words appear frequently in texts but carry little lexical content. - Grammatical Role: These words often serve grammatical purposes rather than conveying specific content. - Non-Discriminative: Stop-words do not help in distinguishing between different classes or categories in text classification tasks.
Files
Steps to reproduce
1. Data Collection from Official Sources. 2. Overview of the previous list of stopwords. 3. Preprocess and clean the collected text. 4. Merge the current list of stopwords with the previous list.