Social Search: Don Quixote Is Alive and Well
January 18, 2013
Here I float in Harrod’s Creek, Kentucky, an addled goose. I am interested in other geese in rural Kentucky. I log into Facebook, using a faux human alias (easier than one would imagine) and run a natural language query (human language, of course). I peck with my beak on my iPad using an app, “Geese hook up 40027.” What do I get? Nothing, Zip, zilch, nada.
Intrigued I query, “modern American drama.” What do I get? Nothing, Zip, zilch, nada.
I give up. Social search just does not work under my quite “normal” conditions.
First, I am a goose spoofing the world as a human. Not too many folks like this on Facebook, so my interests and my social graph is useless.
Second, the key words in my natural language query do not match the Facebook patterns, crafted by former Googlers and 20 somethings to deliver hook up heaven and links to the semi infamous Actor’s Theater or the Kentucky Center.
Social search is not search. Social search is group centric. Social search is an outstanding system for monitoring and surveillance. For information retrieval, social search is a subset of information retrieval. How do semantic methods improve the validity of the information retrieved? I am not exactly sure. Perhaps the vendors will explain and provide documented examples?
Third, without context, my natural language queries shoot through the holes in the Swiss Cheese of the Facebook database.
After I read “The Future of Social Search,” I assumed that information was available at the peck of my beak. How misguided was I? Well, one more “next big thing” in search demonstrated that baloney production is surging in a ailing economy. Optimism is good. Crazy predictions about search are not so good. Look at the sad state of enterprise search, Web search, and email search. Nothing works exactly as I hope. The dust up between Hewlett Packard and Autonomy suggests that “meaning based computing” is a point of contention.
If social search does not work for an addled goose, for whom does it work? According to the wild and crazy write up:
Are social networks (or information networks) the new search engine? Or, as Steve Jobs would argue, is the mobile app the new search engine? Or, is the question-and-answer formula of Quora the real search 2.0? The answer is most likely all of the above, because search is being redefined by all of these factors. Because search is changing, so too is the still maturing notion of social search, and we should certainly think about it as something much grander than socially-enhanced search results.
Yep, Search 2.0.
But the bit of plastic floating in my pond is semantic search. Here’s what the Search 2.0 social crowd asserts:
Let’s embrace the notion that social search should be effortless on the part of the user and exist within a familiar experience — mobile, social or search. What this foretells is a future in which semantic analysis, machine learning, natural language processing and artificial intelligence will digest our every web action and organically spit out a social search experience. This social search future is already unfolding before our very eyes. Foursquare now taps its massive check in database to churn out recommendations personalized by relationships and activities. My6sense prioritizes tweets, RSS feeds and Facebook updates, and it’s working to personalize the web through semantic analysis. Even Flipboard offers a fresh form of social search and helps the user find content through their social relationships. Of course, there’s the obvious implementations of Facebook Instant Personalization: Rotten Tomatoes, Clicker and Yelp offer Facebook-personalized experiences, essentially using your social graph to return better “search” results.
Semantics. Better search results. How does that work on Facebook images and Twitter messages?
My view is that when one looks for information, there are some old fashioned yardsticks; for example, precision, recall, editorial policy, corpus provenance, etc.
When a clueless person asks about pop culture, I am not sure that traditional reference sources will provide an answer. But as information access is trivialized, the need for knowledge about the accuracy and comprehensiveness of content, the metrics of precision and recall, and the editorial policy or degree of manipulation baked into the system decreases.
See Advantech.com for details of a surveillance system.
Search has not become better. Search has become subject to self referential mechanisms. That’s why my goose queries disappoint. If I were looking for pizza or Lady Gaga information, I would have hit pay dirt with a social search system. When I look for information based on an idiosyncratic social fingerprint or when I look for hard information to answer difficult questions related to client work, social search is not going to deliver the input which keeps this goose happy.
What is interesting is that so many are embracing a surveillance based system as the next big thing in search. I am glad I am old. I am delighted my old fashioned approach to obtaining information is working just fine without the special advantages a social graph delivers.
Will today’s social search users understand the old fashioned methods of obtaining information? In my opinion, nope. Does it matter? Not to me. I hope some of these social searchers do more than run a Facebook query to study for their electrical engineering certification or to pass board certification for brain surgery.
Stephen E Arnold, January 18, 2013