View Proposal
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Proposer
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Habte Lejebo Leka
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Title
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Social Media Sentiment Analysis and Visualization System
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Goal
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Description
- The project aims to develop a system for analysing public sentiment in social media posts toward a selected topic, product, or brand. Students will collect and preprocess social media text, handle characteristics such as informal language, emojis, and abbreviations, and develop suitable approaches for sentiment classification. The system will classify posts into positive, negative, and neutral sentiments and provide an interactive dashboard for visualizing sentiment trends and analysing public opinion.
- Resources
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Atandoh, Peter, Zhang Fengli, Daniel Adu-Gyamfi, Habte Lejebo Leka, and Paul Hakeem Atandoh. "A GloVe CNN-BiLSTM Sentiment Classification." 2021 18th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP). IEEE, 2021: 245-249.Dataset: Twitter Sentiment Analysis Dataset Kaggle Link: https://www.kaggle.com/datasets/kazanova/sentiment140
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Background
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Url
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Difficulty Level
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Moderate
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Ethical Approval
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None
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Number Of Students
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2
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Supervisor
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Habte Lejebo Leka
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Keywords
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sentiment analysis, social media analytics, natural language processing, text classification, machine learning, deep learning
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Degrees
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Bachelor of Science in Computational Sciences and Software Engineering