Abstract
The designed and implemented web platform for extracting sentiment from texts consists of a machine learning model retrieving sentiment from a text by categorizing the input into three different classes: positive, negative or neutral. Additionally, this model can be used via a web application processing two different types of text input, namely tweets and (movie) reviews. The web interface allows users to analyze their sentences and evaluate batches of opinions and comments based on specific keywords, retrieved from not one but from various types of online sources, namely Twitter, Reddit, and Youtube. Customizations for additional languages are an additional target.
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Giannakis, S., Valavani, C., Alexandris, C. (2021). A Sentiment Analysis Web Platform for Multiple Social Media Types and Language-Specific Customizations. In: Kurosu, M. (eds) Human-Computer Interaction. Theory, Methods and Tools. HCII 2021. Lecture Notes in Computer Science(), vol 12762. Springer, Cham. https://doi.org/10.1007/978-3-030-78462-1_24
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DOI: https://doi.org/10.1007/978-3-030-78462-1_24
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