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dc.contributor.author
Kapantai, Eleni
en
dc.date.accessioned
2018-05-18T13:34:15Z
dc.date.available
2018-05-19T00:00:16Z
dc.date.issued
2018-05-18
dc.identifier.uri
https://repository.ihu.edu.gr//xmlui/handle/11544/29150
dc.rights
Default License
dc.title
Software for monitoring current trends on Twitter
en
heal.type
masterThesis
en_US
heal.keywordURI.LCSH
Internet marketing
heal.keywordURI.LCSH
Internet advertising
heal.keywordURI.LCSH
Social media
heal.keywordURI.LCSH
Internet--Social aspects
heal.keywordURI.LCSH
Twitter
heal.keywordURI.LCSH
Twitter--Social aspects
heal.keywordURI.LCSH
Online social networks
heal.keywordURI.LCSH
Webometrics
heal.keywordURI.LCSH
Social networks--Research
heal.keywordURI.LCSH
Social sciences-Network analysis
heal.keywordURI.LCSH
Online social networks--Research
heal.keywordURI.LCSH
Data mining
heal.language
en
en_US
heal.access
free
en_US
heal.license
http://creativecommons.org/licenses/by-nc/4.0
en_US
heal.recordProvider
School of Science and Technology, MSc in e-Business and Digital Marketing
en_US
heal.publicationDate
2018-05-18
heal.abstract
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.
en
heal.advisorName
Moridis, Christos
el
heal.committeeMemberName
Ampatzoglou, Apostolos
en
heal.academicPublisher
IHU
en
heal.academicPublisherID
ihu
en_US


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