Exploring user contributed information in social computing systems: quantity versus quality
| Published date | 23 September 2013 |
| Date | 23 September 2013 |
| DOI | https://doi.org/10.1108/OIR-05-2012-0091 |
| Pages | 752-770 |
| Author | Chen Ye,Oded Nov |
| Subject Matter | Library & information science,Information behaviour & retrieval |
Exploring user contributed
information in social computing
systems: quantity versus quality
Chen Ye
Purdue University Calumet, Hammond, Indiana, USA, and
Oded Nov
Polytechnic Institute of New York University, Brooklyn, New York, USA
Abstract
Purpose – The objective of this paper is to explore empirically the relationship between quantity and
quality of user contributed information in online social computing systems, and how these two
performance outcomes are associated with user factors.
Design/methodology/approach – Drawing from prior research, the paper presents a conceptual
model hypothesizing a tradeoff between quality and quantity of user contributed information. In
addition quality and quantity are associated with a set of motivational, cognitive, and social factors.
The model was tested using data obtained through a web-based survey of 345 users of the Flickr
online photo sharing community.
Findings – The empirical results support the hypothesized inverse relationship between quantity
and quality of user contributed information, moderated by user’s tenure in the community. The
findings also suggest that a user’s quantity of contribution is positively associated with the intrinsic
motivation of commitment to the community, whereas quality of contribution is positively associated
with the extrinsic motivation of self-development. While users’ social embeddedness is associated with
quality and quantity of contribution, virtualness of social ties is only associated with quality of
contribution.
Practical implications – The findings of this study can inform the design and management of
online communities, and promote sustained contributions from individual users.
Originality/value – This study extends our knowledge of the quality and quantity of user
contributed online information by demonstrating the inverse relationship between these two
performance outcomes, and that they could be motivated by different user factors.
Keywords Quality, Motivations, Social computing,Online communities, Quantity,
User contributed information
Paper type Research paper
Introduction
In recent years a new breed of online communities – social computing systems – has
emerged. Social computing systems are characterized by the rich exchange of user
generated contents and extensive online social interaction among their members
(Parameswaran and Whinston, 2007a). Some of the best known social computing
systems include content sites such as Wikipedia, Flickr, and YouTube, and social
networks such as Facebook, LinkedIn, and Twitter. The rapid growth of these systems
has attracted the attention of many researchers. Parameswaran and Whinston (2007b,
p. 337), for example, stress that research “needs to evolve to encompass new theories
and methodologies that can address questions posed by social computing, which
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OIR
37,5
752
Received 29 May 2012
First revision accepted
31 July 2012
Online Information Review
Vol. 37 No. 5, 2013
pp. 752-770
qEmerald Group Publishing Limited
1468-4527
DOI 10.1108/OIR-05-2012-0091
extends the scope of usage of information and computing tools to the realm of social
endeavour”.
Sustained participation and content contribution from individual members are
critical for the viability of all online communities (Butler, 2001; Chiu et al., 2006; Farzan
and Brusilovsky, 2011; Koh et al., 2007), and this is particularly the case with social
computing systems, whose contents are contributed entirely by voluntary users. A
number of researchers have investigated the motivations of content contributors
(e.g. Bryant et al., 2005; Fang and Chiu, 2010; Nov et al., 2008; Peddibhotla and
Subramani, 2007). Research on the factors underlying content sharing has primarily
focused on the quantity of contributions (Nov and Ye, 2008), and to date what drives
the quality of user contributions has not been well understood. However the
competitiveness of a virtual community not only depends on the amount of
contributions it attracts, but also on the quality of the contributions it receives (Gu et al.,
2007). In fact quality of postings was found to play a bigger role than posting volume
in user valuation of online discussion boards (Gu et al., 2007).
While quantity and quality are two equally important aspects of user contri butions
in social computing systems, the relationships and differences between these two
performance outcomes have not been given much attention in prior literature. Research
in applied psychology has revealed the tradeoff between quantity and quality as a
fundamental characteristic of human performance in cognitive tasks (Erez, 1990;
Gilliland and Landis, 1992; Locke et al., 1994). In addition individuals’ cognitive
capability and motivation play key roles in determining performance quality and
quantity. Some authors have also argued for a tradeoff between quantity and quality of
contribution in the context of online communities (Gu et al., 2007). However empirical
evidence has provided mixed support for this proposition (Gu et al., 2007; Peddibhotla
and Subramani, 2007; Wasko and Faraj, 2005).
In light of the theoretical and practical value of a deeper understanding of quantity
and quality of user contributions, the overall objective of the present study is to extend
the relevant research on human performance and virtual communities to social
computing systems, and explore the following research questions:
RQ1. What is the relationship between quantity and quality, the two performance
outcomes of contributions?
RQ2. How does users’ cognitive capability influence quantity and quality of
contributions?
RQ3. What are the motivational and social factors influencing quantity and
quality of contributions?
Prior studies and research hypotheses
Quality vs quantity
Human performance in cognitive tasks has been one of the focuses of research on
human decision making. Performance in many simple tasks is reflected by the speed at
which a given task is accomplished, i.e. the quantity of work done in a certain amount
of time. Most cognitive tasks performed in real life, however, are complex tasks that
need to be evaluated not only by quantity, but also by the quality of work completed.
As noted by Erez, “Quality refers to a degree of excellence of what is produced, and it
can be clearly distinguished from quantity, which refers to the total amount of what is
Social computing
systems
753
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