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SmartData Collective > Big Data > Data Mining > Why Questions are Becoming More and More Popular in the Social Realm
Data Mining

Why Questions are Becoming More and More Popular in the Social Realm

Daniel Tunkelang
Daniel Tunkelang
7 Min Read
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Yahoo! Answers and Answers.com have been around since 2005.

Yahoo! Answers and Answers.com have been around since 2005. But community question answering (as distinct from question answering using natural language processing) has witnessed a resurgence of popularity–at least in the blogosphere and among investors. Quora and Hunch are two of hottest startups on the web, and Aardvark was acquired by Google earlier this year. Most recently, Ask.com relaunched with a return to its question-answering roots and Facebook began rolling out Facebook Questions.

So there’s no question that community question answering is hot. The question is why? In particular, is community question answering a step forward or backward relative to today’s search engines, or is it something different?

Regarding Facebook Questions, Jason Kincaid writes in TechCrunch:

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Given its size, it won’t take long for Facebook to build up a massive amount of data — if that data is consistently reliable, Questions could turn into a viable alternative to Google for many queries.

That’s a big if.  But I think the bigger caveat is the vague quantifier “many”. The success of community question answering services will depend on how these services position themselves relative to users’ information needs. Anyone arguing that these services can or should replace today’s web search engines might want to consider the following examples of information needs that are typical of current search engine use:

  • How do I get an iPhone case?
  • Who sings the “choco latte” song?
  • What movies are playing in my neighborhood?
  • How do I get to Boston from New York?
  • What is the best selling netbook?
  • Who offers the best cell phone reception in New York?
  • What was the score in the North Korea – Portugal game?

I hope I don’t have to keep going to convince you that web search engines have earned their popularity by serving a broad class of information needs (i.e., answer lots of questions)–and that’s without even using the wide variety of personalized and social features that web search engines are rapidly developing.

The common thread in the above questions is that they focus on objective information. In general, such questions are effectively and efficiently answered by search engines based on indexed, published content (including “deep web” content made available to search engines via APIs). There’s a lot of work we can do to improve search engines, particularly in the area of supporting query formulation. But it seems silly and wasteful to route such questions to other people–human beings should not be reduced to performing tasks at which machines excel.

That said, I agree with Kincaid that there are many information needs that are well addressed by  community question answering. In particular:

  • Questions for which point of view is a feature, not a bug. Review sites succeed when they provide sincere, informed personal reactions to products and services. Similarly, routing questions to people makes sense either when we care about the answerer’s a point of view. For some questions, I want the opinion of someone who shares my taste (which is what Hunch is pursuing with its “taste graph“). For others, I want a diversity of expert opinions–for which I might turn to Aardvark (which tries to route questions to topic experts), Quora (where people follow particular topics), or LinkedIn Answers. Over time, the answers to many such questions can be published and indexed–and indeed some answers sites receive a large share of their traffic from search engines.
  • Niche topics. As much as web search as improved information accessibility for the “long tail” of published information, the effectiveness of web search can be highly variable for the most obscure information needs. Moreover, this effectiveness depends significantly on the user: some people are better at searching than others, especially in their areas of domain expertise. Social search can help level the playing field. Much as Wikipedia has surfaced much of the expertise at the head of the information distribution, community question answering can help out in the tail.
  • Community for its own sake. Even in cases where search engines are more effective and efficient than community question answering services, some people prefer to participate in a social exchange rather than to conduct a transaction with an impersonal algorithm. Indeed, researchers at Aardvark found that many of the questions posed through their service (pre-acquisition) could be answered successfully using Google. I’ll go out on a limb and assume that Aardvark’s users were early technology adopters who are quite conversant with search engines–but in some case chose to use a social alternative simply because they wanted to be social.

Conclusions? Community question answering may be overhyped right now, but it isn’t a fad. There are broad classes of subjective information needs that require a point of view, if not a diversity of views. And even if much of the use of community question answering sites is mediated by search engines indexing their archives, there will always be a need for fresh content. I also believe that social search will continue to be valuable for niche topics, since neither search engines nor searchers will ever be perfect.

But I think the biggest open question is whether people will favor community question answering simply to be social. I conjecture that, by very publicly integrating community question answering into is social networking platform, Facebook is testing the hypothesis that it can turn information seeking from a utilitarian individual task into an entertaining social destination. Given Facebook’s highly engaged user population, we won’t have to wait long to find out.

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