Author(s): Harmanpreet Singh | Harpreet Kaur Rana
Journal: International Journal of Digital Library Services
ISSN 2250-1142
Volume: 1;
Issue: 2;
Start page: 32;
Date: 2011;
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Keywords: Social network | egocentric | sociocentric | rural faculty | performance
ABSTRACT
In this paper, we introduce social network analysis for investigating the effect of Information and Communication Technology (ICT) use on the performance of the faculty in Engineering Colleges in rural India. Here, we highlight the data collection procedure, its benefits and limitations and standard measures of social network data. We first suggest that collection and analysis of relational and attribute data offers richer insights with regards to the investigation of structural effects of network position on performance of Engineering faculty. Second, drawing from theoretical and methodological strengths of previous studies conducted in Social Network, we describe the process for collecting relational data from the faculty members in isolated and rural settings. We primarily discuss two specific types of social network data collection approaches-- (i) whole network and (ii) ego-centric network approach; and highlight its opportunities and challenges. Third, we discuss the problem of network sampling in the context of faculty members in rural areas. Finally, challenges associated with analysing social network data are presented.
Journal: International Journal of Digital Library Services
ISSN 2250-1142
Volume: 1;
Issue: 2;
Start page: 32;
Date: 2011;
VIEW PDF
DOWNLOAD PDF Original pageKeywords: Social network | egocentric | sociocentric | rural faculty | performance
ABSTRACT
In this paper, we introduce social network analysis for investigating the effect of Information and Communication Technology (ICT) use on the performance of the faculty in Engineering Colleges in rural India. Here, we highlight the data collection procedure, its benefits and limitations and standard measures of social network data. We first suggest that collection and analysis of relational and attribute data offers richer insights with regards to the investigation of structural effects of network position on performance of Engineering faculty. Second, drawing from theoretical and methodological strengths of previous studies conducted in Social Network, we describe the process for collecting relational data from the faculty members in isolated and rural settings. We primarily discuss two specific types of social network data collection approaches-- (i) whole network and (ii) ego-centric network approach; and highlight its opportunities and challenges. Third, we discuss the problem of network sampling in the context of faculty members in rural areas. Finally, challenges associated with analysing social network data are presented.
