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dc.contributor.author
Keikoglou, Georgios
en
dc.date.accessioned
2015-06-23T12:48:48Z
dc.date.available
2015-09-27T05:58:25Z
dc.date.issued
2015-06-23
dc.identifier.uri
https://repository.ihu.edu.gr//xmlui/handle/11544/486
dc.rights
Default License
dc.title
Text mining in social media for participatory sensing data
en
heal.type
masterThesis
heal.keyword
Data mining
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heal.keyword
Dissertations, Academic
en
heal.language
en
heal.access
free
el
heal.license
http://creativecommons.org/licenses/by-nc/4.0
heal.recordProvider
School of Science and Technology, MSc in Information & Communication Technology Systems
heal.publicationDate
2011-10
heal.bibliographicCitation
Keikoglou Georgios, 2011, Text mining in social media for participatory sensing data ,Master's Dissertation, International Hellenic University
en
heal.abstract
This dissertation was written as a part of the MSc in ICT Systems at the International Hellenic University. The main goal of the dissertation was to discover text mining tools in order to use them in social media and social networks for participatory sensing reasons. Environmental issues are around us each time of day and for that reason it is necessary to identify them using available text mining tools. It is a fact that there is a lack of available text mining software for social networks for use because companies use them for personal or research purposes only. For that reason two internet text mining tools have been used for the completion of this dissertation. The objective of the current dissertation is to monitor social media and a specific social network for participatory sensing issues. The main idea of participatory sensing is to gather information from individuals and then try to derive/create/disseminate useful knowledge about issues that concern all of us and most of the times about the environment. In line with the adopted methodology, specific keywords have been searched followed by geographical assessment of the town of Thessaloniki in order to acquire information of that specific area. An internet web tool called “Social Mention” has been used for all social media and another web tool called “Trending” has been used for Twitter. The results of both web internet tools generated interesting information about environmental issues and problems showing that quite a few issues like waste and garbage management, concern Greek society and especially the town of Thessaloniki. With the participation of citizens and access in environmental information, a more safe and healthy environment is possible in the future. At this point, I would like to thank my supervisor Professor Kostas Karatzas for his confidence in me and for the valuable guidance throughout the preparation of my dissertation. I would like also to thank Ms. Marina Riga which was by my side the entire time of the dissertation and help me out with her patience. Last but not least, I would like to thank my family for their love and support.
en
heal.tableOfContents
DISCLAIMER ....................................................................................................................... 3 ABSTRACT .......................................................................................................................... 4 1 Introduction ............................................................................................................... 7 2 Participatory sensing .................................................................................................. 8 2.1 Participatory sensing process ..................................................................................... 9 2.2 Mobile phones and Sensors ..................................................................................... 11 2.3 Participation of citizens ............................................................................................ 12 2.4 Participatory Sensing Projects .................................................................................. 13 3 Social Media ............................................................................................................. 16 3.1 Social Media Description .......................................................................................... 16 3.2 Categorization of social media ................................................................................. 18 3.2.1 Online Social Communities ............................................................................... 18 3.2.2 Blogs .................................................................................................................. 19 3.2.3 Podcasts ............................................................................................................. 20 3.2.4 Forums ............................................................................................................... 21 3.2.5 Wikis .................................................................................................................. 21 3.2.6 Content communities ........................................................................................ 22 4 Information Analysis ................................................................................................. 23 4.1 Data Mining .............................................................................................................. 23 4.1.1 Data Mining Process .......................................................................................... 24 4.1.2 Mined Data ........................................................................................................ 26 4.2 Text Mining ............................................................................................................... 27 4.2.1 Text Mining Process .......................................................................................... 28 5 Mining in Social Media .............................................................................................. 30 5.1 Web Content Mining ................................................................................................ 31 5.2 Web Usage Mining.................................................................................................... 31 5.3 Web Structure Mining .............................................................................................. 31 6 Mining citizen’s observations in Social Network........................................................ 33 6.1 Twitter ...................................................................................................................... 33 6.2 Twitter Statistics ....................................................................................................... 35 7 Text mining methodology ......................................................................................... 37 7.1 Available Text Mining tools ...................................................................................... 38 7.1.1 Social Mention ................................................................................................... 39 7.1.2 Trending ............................................................................................................ 75 8 Discussions of results ................................................................................................ 90 8.1 Social Mention .......................................................................................................... 90 8.1.1 Type of information ........................................................................................... 93 8.1.2 Authors .............................................................................................................. 96 8.1.3 Sentiment .......................................................................................................... 96 8.2 Trending .................................................................................................................... 97 8.2.1 Posts ................................................................................................................ 100 8.2.2 Time Line ......................................................................................................... 101 8.3 Correlation of results based on surveys ................................................................. 102 9 Conclusions............................................................................................................. 104 BIBLIOGRAPHY ............................................................................................................... 105
en
heal.advisorName
Karatzas, Prof. Kostas
en
heal.committeeMemberName
Karatzas, Kostas
en
heal.committeeMemberName
Vlahavas, I.
en
heal.committeeMemberName
Barsakelis, Hristu
en
heal.academicPublisher
School of Science &Technology, Master of Science (MSc) in Information and Communication Systems
en
heal.academicPublisherID
ihu
heal.numberOfPages
109
heal.fullTextAvailability
true


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