IMPACT AND CHALLENGES OF NATURAL LANGUAGE PROCESSING (NLP) FOR SENTIMENT ANALYSIS IN SOCIAL MEDIA
DOI:
https://doi.org/10.59795/ijersd.v6i1.176Keywords:
Natural Language Processing, Sentiment Analysis, Social MediaAbstract
This study is a descriptive survey research design the explored the impact and challenges of Natural Language Processing (NLP) for sentiment analysis in social media and sought to contribute to the development of more accurate and reliable sentiment analytical tools. Two research questions and two null hypotheses guided this study. The instrument for data collection was Research-made questionnaire titled Impact and Challenges of Natural Language Processing (ICNPL) which was adequately validated by three experts and the reliability co-efficient obtained at 0.82 by the cronbach alpha method. The questionnaire was administered on 400 Respondents comprising of 200 Lecturers and 200 Students of five tertiary institutions in Northern Nigeria which were randomly selected. The mean score and standard deviation were used to answer the research questions and z- test statistical tool was adopted in testing the hypotheses. It was discovered that NLP is impactfu in sentiment analysis and it has revolutionalised sentiment analysis in social media by enabling computers to understand and interpret human language leading to numerous benefits with some challenges persisting. The researcher recommended among other things that NLP should be continuously updated to keep pace with incessant changes inherent with social media platforms and that there should be continuous research in NLP and sentiment analysis so as to be acquainted what it takes to address emerging challenges
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