Unit:
Κατεύθυνση Διαχείριση Δεδομένων, Πληροφορίας και ΓνώσηςΠληροφορική
Author:
Giannakis Stavros
Supervisors info:
Χριστίνα Αλεξανδρή, Αναπληρώτρια Καθηγήτρια, Τμήμα Γερμανικής Γλώσσας και Φιλολογίας (Εξωτερικό Μέλος ΔΕΠ Τμήματος Πληροφορικής και Τηλεπικοινωνιών), Εθνικό και Καποδιστριακό Πανεπιστήμιο Αθηνών
Original Title:
Sentiment Analysis Application with Social Media Network Integration
Translated title:
Sentiment Analysis Application with Social Media Network Integration
Summary:
Sentiment Analysis is an application domain of Natural Language Processing focusing in extracting sentiment and opinion from textual input. The purpose of the present Thesis is the creation of a web platform for extracting sentiment from texts. Specifically, the designed and implemented platform consists of a machine learning model that manages to retrieve 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 platform also provides the possibility to retrieve comments and opinions from different social media platforms such as Reddit, Twitter and Youtube by searching any keyword and classify the results. The results are presented with a distinctive visualization to the users, giving a better perspective of what people think about specific topics. For the development of the components of the present project and application, the Python and JavaScript programming languages have been utilized. The machine learning model and the training data is described, as well as the preprocessing techniques that each textual input is subjected to before its classification into a category. Finally, improvements on the platform are proposed for offering more options and functionalities to the users.
Main subject category:
Technology - Computer science
Keywords:
Text Classification, Web Development, Sentiment Analysis, Opinion Mining, Machine Learning, Natural Language Processing
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