Paper Info
Title
Complementary Integration of Heterogeneous Crowd-Sourced Datasets for Enhanced Social Analytics
Abstract
On behalf of the rapidly and widely disseminated smartphone technology into the public, lots of social network sites and location-based social applications are accumulating a huge volume of massive crowd's daily experiences and thoughts in an unprecedented scale. We can regard them as novel data sources for accomplishing various social analytics, which have usually required lots of efforts to collect crowds' opinion and behavioral data. Thus, we can take advantages of abundant social datasets by integrating them appropriately. However, when we integrate disparate sources to derive a comprehensive view for a survey, it is necessary to know intrinsic exclusive values of each data source compared to others in an intuitive and succinct way. In fact, lots of efforts and time are wasted to overview various datasets consequently to confidently choose a dataset to be integrated in a final result. In this paper, we propose a complementarity index, which can estimate the exclusive usefulness of data sources in terms of spatial and topical coverage when selecting data sources for social analytics purposes. We conducted an experiment about complementarity measurement with two real social datasets from Twitter and VoiceTra; the latter is a speech-to-speech translation app, with which we can additionally obtain crowds' verbal translation logs. With the proposed complementarity index, we can measure the capability of a dataset comparing to others before integrating datasets, thus enabling analysts to examine much more datasets from as many related data sources as possible by focusing on exclusive coverage and relative strength of relevant topics.
Year
DOI
Venue
2013
10.1109/MDM.2013.100
MDM (2)
Keywords
Field
DocType
social analytics,social datasets,complementarity measurement,social network site,crowd lifelogs,voicetra,data source,smartphone technology,crowd verbal translation logs,real social datasets,mobile applications,enhanced social analytics,abundant social datasets,social network sites,social analysis,topical coverage,twitter,complementary integration,spatial coverage,location-based social application,social analytics purpose,complementarity measumement,heterogeneous crowd-sourced datasets,various social analytics,related data source,behavioral data,speech-to-speech translation app,smart phones,social networking (online),novel data source,mobile computing,crowd opinion,location-based social applications,complementarity index,time measurement,indexes,mobile communication,temperature measurement,internet
Complementarity (molecular biology),Data science,Mobile computing,Crowds,World Wide Web,Social network,Computer science,Relative strength,Social analytics,Mobile telephony,The Internet,Distributed computing
Conference
Volume
ISBN
Citations 
2
978-1-4673-6068-5
0
PageRank 
References 
Authors
0.34
4
5
Name
Order
Citations
PageRank
Ryong Lee141234.22
Kyoung-Sook Kim22414.07
Komei Sugiura317219.36
Koji Zettsu421239.07
Yutaka Kidawara515127.45