Implementation of Lexicon-based Sentiment Analysis on Greek Text Data

The particular thesis was implemented in the context of my undergraduate studies at the Athens University of Economics and Business, in the Department of Management Science and Technology, during the spring semester 2018–'19. The thesis is a combination of:

• the final report of my internship at isMOOD Data Technology Services company, and
• literature review associated with the project I worked on during this internship.

isMOOD is a Greek B2B company in the field of text analytics, providing services through an in-house platform and customised reports. The asset of the company lies in the application of sentiment analysis on text data coming from various social media sources (e.g. Facebook, Twitter, Instagram, YouTube, news sites, forums, blogs).
As a Back-end Developer intern at isMOOD I implemented a lexicon-based approach for performing sentiment analysis on Greek text data. The technologies I used were Python 2.7 and MongoDB.

Supervisors:

• Academic: Prof. Diomidis Spinellis
• Company: Stauros Triantafyllos (Lead Software Engineer)

Abstract

An important part of our information-gathering behaviour has always been to find out what other people think. With the growing availability and popularity of opinion-rich resources such as online review sites, personal blogs and social media channels, new opportunities and challenges arise as people now can, and do, actively use information technologies to seek out and understand the opinions of others. The sudden eruption of activity in the area of opinion mining and sentiment analysis, which deals with the computational treatment of opinion, sentiment, and subjectivity in text, has thus occurred at least in part as a direct response to the surge of interest in new systems that deal directly with opinions as a first-class object.
This thesis aims to provide a literature review on sentiment analysis, the widespread available methods for its application to text data, with an emphasis on lexicon-based approaches for the Greek language. In addition, a particular methodology is proposed and implemented in the context of an internship, for the application of lexicon-based sentiment analysis to Greek text data, which facilitates from a well-reputed English sentiment lexicon by translating it into Greek and transferring sentiment to a Greek lexicon.