Σύστημα γεωγραφικής απεικόνισης δεδομένων κοινωνικών δικτύων με εφαρμογή στην εκπαίδευση
A system for geographic visualization of social data with application in education
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Keywords
Διαδίκτυο ; Κοινωνικά δίκτυα ; Μέσα κοινωνικής δικτύωσης ; Υπηρεσίες Ιστού ; Γεωγραφικά Συστήματα Πληροφοριών ; Twitter ; Learning analyticsAbstract
The continuous development of the Internet in recent years has brought significant changes in many areas of society. The phenomenon of social networking through the internet nowadays, has assumed enormous dimensions and has gained great power, in almost all areas of everyday life (information, entertainment, politics, economy, trade, education etc.).
The purpose of this thesis is the content’s emergence of social media, as a source of voluntary geographic information. Specifically, it focuses on Twitter, the most popular social networking tool for publishing short messages. The large number of tweets that are published daily worldwide, the restriction of the messages’ characters and the possibility of referring every tweet’s location (geolocated tweets), are strong indications for the significance of content’s use, so that useful results will be exported in various areas of everyday life.
The present thesis attempted, through the development of a system, to collect data from Twitter’s platform, which they contain the location’s information they have been posted from. With their projection on the map, is accomplished the immediate utilization by each user, in the corresponding field of his occupation. In addition, the method of Learning Analytics is presented. According to this, may be performed the analysis and presentation of the collected data, aiming the optimization of learning process and the environment that is conducted.
For the collection of the results, the REST API and Streaming API were used. According to the collected results, minimum data contained the geographical information which is necessary for their projection on the map. Thus, RESTful Web Service of Bing Maps was used, in order to achieve the finding and linking the geographical information in each tweet.