This dissertation was written as a part of the MSc in
E
-
Business and Digital Marketing
at the International Hellenic University
by student Kapantai Eleni under the supervision
of Prof.Ch.Moridis.
Data lied in Social Networks can provide useful information for research purposes,
along with valuable knowledg
e concerning user’s behavior. Context (e.g. preferences,
opinions, intent, sentiment, activities) provided by social data cannot be reached by
traditional research methods, helping to understand and interpret Social Media traffic
on a more holistic level.
By this master thesis we intend to develop a system
that uses
Twitter to understand how people are feeling about a topic that we choose. Primarily,
we scroll the Twitter and
gather information from the well
-
known platform
on
given
queries. On the way forwa
rd, our efforts focused on the classification of those messages
with respect to their sentiment, applying data mining techniques. The ideal of this work
lies in the recognition of current trends on Twitter through the extraction of high
-
valued
information
dealing with any potential challenge that may arise.
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