Being a millennial is coming handy at work today immensely. I’ve seen IRC, Yahoo Chat Rooms, GTalk, Orkut, Facebook, IRC, MSN Messenger, Yahoo Messenger, third party messaging platforms like Miranda, Pidgin, IRC and now Slack. (What am I missing?) Of course, there have also been dating (and messaging?) apps like Tinder, Plenty Of Fish, OkCupid and the like.
Woo’s TagSearch lets users search by attributes
Among the hoard of dating apps out there, Woo has introduced a feature called TagSearch which lets its users discover other people based on interests and attributes like home town, college, political leaning and favourite actor among others. It has also added a feature called QuestionCast where users can ask questions and invite other users to share their views on the same. (Note that the third image in the collage above is where the tag ‘Mercedes Benz India’ was highlighted and Woo showed up profiles of users who had liked the page on Facebook.)
Remember Facebook’s Graph Search? Neither do we
Basically, Woo has ventured into the territory that Facebook promised with Graph Search . However, Facebook’s Graph Search did not take off the way it had intended and the company ceased working on it. The Graph Search was a semantic search engine designed to provide answers instead of links through natural language queries. It set out to display data from over 1 billion users combined with external data into a search engine providing user specific search results. The algorithm would find this info from a user’s friend network.
Proactive filtering VS information consumption
Woo’s TagSearch works by hyperlinking users’ information in the form of a tag and clubbing those tags to provide results based on users who have included that particular tag on their profile. It is a great feature to have in a dating app where the user is pretty much restricted to hitting ‘like’ or ‘dislike’ on potential match profiles.
Not enough info to tag yet
In a user’s profile, things like the hometown, religion, work area, education, likes, Orkut like attributes like lifestyle choices (smoking, drinking, food preferences), ‘passions and interests’ like travel (I travel whenever I can), movies (picky but passionate) and music (I love all kinds of music) are clickable. However, it seems that Woo does not yet have enough data to implement this feature since most of the tags I clicked on were throwing up a ‘no more people from XYZ tag’ message after searching for ‘people who like XYZ’. In that, the app crashes a few times while trying to get this data.
The idea is undoubtedly interesting, it could possibly change the way filtering happens in a more proactive manner when seeking other users in dating apps. But it probably needs a whole lot of users as well as their data to club these attributes as tags. Other than that, if a user enters unlikely text like “I @m a grt M!Ley CyRu$ fan” with special characters and symbols, it will crowd the tag space with individual tags which will not provide tags clubbed “I am a Miley Cyrus fan” and cause not just duplications but also noise and confusion for the algorithm. Let’s see how this goes.