Identifying and predicting the desire to help in social question and answering

an article by Zhe Liu (IBM Almaden Research Center, San Jose, CA, USA) and Bernard J. Jansen (Qatar Computing Research Institute, Doha, Qatar) published in Information Processing & Management Volume 53 Issue 2 (March 2017)

Highlights

• Evaluate the effectiveness of question routing systems in the social Q&A process.
• Find that individuals are more willing to share their knowledge under question routing context whereas less connected.
• Build an effective model to automatically identify active knowledge sharers from non-shares using non-Q&A features from four dimensions: profile, posting behavior, language style, and social activities.

Abstract

The increasing volume of questions posted on social question and answering sites has triggered the development of question routing services. Most of these routing algorithms are able to recognize effectively individuals with the required knowledge to answer a specific question.

However, just because people have the capability to answer a question, does not mean that they have the desire to help.

In this research, we evaluate the practical performance of the question routing services in social context by analyzing the knowledge sharing behavior of users in social Q&A process in terms of their participation, interests, and connectedness. We collect questions and answers over a ten-month period from Wenwo, a major Chinese question routing service.

Using 340,658 questions and 1,754,280 replies, findings reveal separate roles for knowledge sharers and consumers. Based on this finding, we identify knowledge sharers from non-sharers a priori in order to increase the response probabilities.

We evaluate our model based on an analysis of 3006 Wenwo knowledge sharers and non-sharers.

Our experimental results demonstrate knowledge sharer prediction based solely on non-Q&A features achieves a 70% success rate in accurately identifying willing respondents.

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Understanding the online information-seeking behaviours of young people: the role of networks of support

an article by R. Eynon and L.-E. Malmberg (University of Oxford, UK) published in Journal of Computer Assisted Learning Volume 28 Issue 6 (December 2012)

Abstract

Information seeking is one of the most popular online activities for young people and can provide an additional information channel, which may enhance learning.

In this study, we propose and test a model that adds to the existing literature by examining the ways in which parents, schools, and friends (what we call networks of support) effect young people’s online information behaviours, while at the same time taking into account young people’s individual characteristics, confidence, and skills to use the Internet.

Using path analysis, we demonstrate the significance of networks of support in understanding the uptake of online information seeking both directly and indirectly (through enhancing self-concept for learning and online skills).

Young people who have better networks of support, particularly friends who are engaged in technology, are more likely to engage in online information seeking.

While quantitative models of this nature cannot capture the complexity of individual online search practices, these findings may assist in the development of policy and practice to support young people to make the most effective use of the Internet for information seeking.

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