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PredectivePluse: Sentiment Analysis for Market Prediction

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dc.contributor.author Edirisooriya, Akhila
dc.date.accessioned 2026-03-23T05:37:52Z
dc.date.available 2026-03-23T05:37:52Z
dc.date.issued 2025
dc.identifier.citation Edirisooriya, Akhila (2025) PredectivePluse: Sentiment Analysis for Market Prediction. BSc. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 2019037
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/3019
dc.description.abstract This paper tackles the challenge of predicting stock market trends by integrating sentiment analysis with Long Short-Term Memory (LSTM) networks. Traditional methods, relying on historical price data, often overlook the immediate impact of market sentiment on stock movements. To address this, the author incorporate real-time sentiment data from sources such as social media and financial news, using advanced natural language processing techniques to extract actionable sentiment indicators. en_US
dc.language.iso en en_US
dc.subject Stock Market Prediction en_US
dc.subject Sentiment Analysis en_US
dc.subject LSTM Networks en_US
dc.title PredectivePluse: Sentiment Analysis for Market Prediction en_US
dc.type Thesis en_US


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