User Behavior Patterns Within Social Q&A Services

A number of studies have investigated users’ behavior patterns at the aggregate level by analyzing large sets of activity data obtained from various social Q&A services, suggesting several common patterns. In general, it appears that little overlap exists between those who ask questions and those who answer questions on social Q&A services.

Nam et al.’s (2009) analysis of Naver Knowledge-iN’s data revealed that only 5.4% of that site’s users engaged in both asking and answering in the same category, showing that users were largely divided into askers and answers. Shah et al. (2008) found that users at higher levels on Yahoo! Answers seemed to be answering many questions, but not necessarily posing that many questions, while those at lower levels tended to be mostly asking questions. Similarly, Kang, Kim, Gloor, and Bock (2011) identified that at both Yahoo! Answers and Knowledge-iN, heavy users tended to answer questions, spending little time asking questions.

However, some overlap has been observed in topical categories that mostly attract non-factual questions. Adamic et al. (2008) found that technical categories such as Car Maintenance & Repair or Computers & Internet had a lower overlap in users who were both askers and answerers, while categories dealing with familiar topics such as Family & Relationships had the highest overlap between the two roles.

Compared to askers, answerers demonstrate much greater commitment to social Q&A communities by contributing more and staying longer. Shah et al. (2008) found that in Yahoo! Answers, users who had earned more points and thus were at higher levels exhibited more and better participation by answering more questions and receiving higher ratings on average than those at lower levels. Those who answered questions not only demonstrated greater participation but also showed greater retention than those who asked questions, as users who stayed longer prefer answering to asking (Yang et al., 2010).

In addition, as in many other online communities, use of social Q&A services follows a power-law distribution. Furtado, Andrade, Oliveira, and Brasileiro (2013) confirmed the power-law distribution of users in the context of social Q&A by analyzing data obtained from five sites that operated based on the Stack Exchange Q&A platform. Similarly, Welser, Gleave, Barash, Smith, and Meckes (2009) found that contributions to Live QnA follow a skewed distribution, with those at the top 1 % activity level posting over 70% and those at the top 10% activity level posting over 95 % of all posts.

While some may continue to use the site, among the total group of those who use social Q&A sites to address their information needs, some may ask a question and then never return to the site. Yang et al.’s (2010) study reported that a large proportion of people who ask a question on a social Q&A site tend to be one-time users, with 30% - 70% of users leaving after posting just once.

Research findings indicate that one’s decision regarding whether to continue to use a social Q&A site after asking a question is influenced by one’s experience with the site. Yang et al. (2010) examined users’ participation lifespans across three social Q&A sites, Yahoo! Answers, Naver Knowledge-IN, and Baidu Knows, and found that first experiences mattered for user retention. According to Yang et al., question askers tended to stay longer if they could successfully obtain better, more numerous, and longer

responses. Kim (2010) also found that previous positive experiences with Yahoo!

Answers motivated users to use it as an information source again. Overall, it seems that a very small number of users continue to use social Q&A services, while most people are one-time users, and those who participate in communities usually do so intermittently (Furtado et al., 2013; Nam et al., 2009).

With regard to the behavioral patterns of those who answer questions, they tend to specialize in answering questions (Nam et al., 2009). However, this is not the case for those who specialize in providing technical answers (Welser et al., 2009). This may be partly attributed to the fact that the posting of opinion and discussion-type questions that may be considered trivial and non-serious predominates (Welser et al., 2009). Adamic et al.’s (2008) study confirmed this tendency towards less seriousness on Yahoo! Answers. They suggested that the questions on Yahoo! Answers are very shallow despite the broadness of its topics.

In addition, dedicated experts who contribute primarily technical and factual answers are rare, partly because they get crowded out by the high activity of less serious contributors (Welser et al., 2009). Furthermore, social Q&A sites seem to demonstrate relatively poor performance in answering technical questions that require domain

expertise (Nam et al., 2009). Some users of Yahoo! Answers perceive that a social Q&A site is not a good place to ask serious or focused technical questions (Kim, 2010).

Users’ behavioral patterns seem to be influenced by several factors, including cultural differences and topical categories. Researchers have reported differences in user behavior patterns in social Q&A services between the West and East. Kang et al. (2011) showed that on Yahoo! Answers, a U.S. social Q&A service, users answer any questions on which they have opinions, even though their answers might overlap with other

answers or not provide unique contributions, while at Knowledge iN, a Korean social Q&A service, if questions are correctly answered once, other heavy users rarely post more answers to these questions. Yang et al. (2010) also found that there are more social conversations going on on Yahoo! Answers compared to other social Q&A services, and that Yahoo! Answers has significantly more answers per question on average. They argued that Yahoo! Answers users like to raise discussion topics to garner others’

opinions or simply for fun, and they tend to add more humor, offer personal opinions, and express sociable statements on the answering side.

With respect to the effect of topical categories on user behavior patterns, Adamic et al.’s (2008) study showed that responses on Yahoo! Answers exhibit different

characteristics and dynamics depending on topic categories. Based on an analysis of its activity data, the researchers classified categories on Yahoo! Answers into three topic

types: Factual, Advice, and Discussion. Each of the three types displays different

characteristics in terms of thread length and thread depth. For example, questions posted in a Factual category such as Computers & Internet tend to have a few long replies, while questions posted in an Advice or Discussion category such as Family & Relationships and Sports tend to have many replies with moderate length.