dc.contributor.author | Efstathiades, Hariton | en |
dc.contributor.author | Antoniades, Demetris | en |
dc.contributor.author | Pallis, George C. | en |
dc.contributor.author | Dikaiakos, Marios D. | en |
dc.creator | Efstathiades, Hariton | en |
dc.creator | Antoniades, Demetris | en |
dc.creator | Pallis, George C. | en |
dc.creator | Dikaiakos, Marios D. | en |
dc.date.accessioned | 2019-11-13T10:39:58Z | |
dc.date.available | 2019-11-13T10:39:58Z | |
dc.date.issued | 2017 | |
dc.identifier.isbn | 978-1-5090-4607-2 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/53889 | |
dc.description.abstract | The popularity and huge amount of information published in Online Social Networks (OSN) established them as one of the main data sources for a variety of research community fields. However, the design of a large-scale dataset collection campaign is a major problem for organizations and researchers who aim in addressing their research questions by analyzing this type of data. OSN platforms provide Application Programming Interfaces (API) to third party developers, which enable them to retrieve and use this data for applications deployment. However, due to OSN imposed limitations, the process of retrieving large scale data with the use of these APIs is challenging and time consuming, resulting in datasets which are either incomplete or outdated. It is relatively impossible for an individual scientist or research group to follow an efficient dataset collection procedure and build a large sample in a short amount of time. In this paper we present a framework for efficient crowd crawling of OSN. Our framework is based on the use of multiple OSN accounts, which are engaged in an efficient distributed collection process able to circumvent the imposed limitations without violating the terms of use. We present an evaluation of the proposed solution and demonstrate its performance in terms of dataset completeness and timeliness, for the case study of Twitter, one of the most popular platforms used in research. © 2016 IEEE. | en |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en |
dc.source | Proceedings - 2016 IEEE 2nd International Conference on Collaboration and Internet Computing, IEEE CIC 2016 | en |
dc.source | 2nd IEEE International Conference on Collaboration and Internet Computing, IEEE CIC 2016 | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85013188444&doi=10.1109%2fCIC.2016.056&partnerID=40&md5=a51af2e9b55f8dcbf071583750b625d1 | |
dc.subject | Amount of information | en |
dc.subject | Data acquisition | en |
dc.subject | Application programming interfaces (API) | en |
dc.subject | Social networking (online) | en |
dc.subject | Research communities | en |
dc.subject | On-line social networks | en |
dc.subject | Online social networks | en |
dc.subject | Distributed collections | en |
dc.subject | Distributed data | en |
dc.subject | Distributed data collection framework | en |
dc.subject | Large-scale dataset | en |
dc.subject | Large-scale dataset collection | en |
dc.subject | Online social networks (OSN) | en |
dc.subject | Research questions | en |
dc.title | Distributed large-scale data collection in online social networks | en |
dc.type | info:eu-repo/semantics/conferenceObject | |
dc.identifier.doi | 10.1109/CIC.2016.056 | |
dc.description.startingpage | 373 | |
dc.description.endingpage | 380 | |
dc.author.faculty | 002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences | |
dc.author.department | Τμήμα Πληροφορικής / Department of Computer Science | |
dc.type.uhtype | Conference Object | en |
dc.description.notes | <p>Sponsors: Drexel University | en |
dc.description.notes | RMIT | en |
dc.description.notes | University of Pittsburgh | en |
dc.description.notes | University Zhejiang University | en |
dc.description.notes | Conference code: 125951</p> | en |
dc.contributor.orcid | Pallis, George C. [0000-0003-1815-5468] | |
dc.contributor.orcid | Dikaiakos, Marios D. [0000-0002-4350-6058] | |
dc.gnosis.orcid | 0000-0003-1815-5468 | |
dc.gnosis.orcid | 0000-0002-4350-6058 | |