Meena Nagarajan                      

Why do People Write - The Intention Landscape

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Of the several messages that users post on social media everyday, an important task for an application trying to respond to a message is to identify the underlying intent. My work in the identification of intents behind user posts caters to monetization of user activity on social networks [WI09]. Unlike web search, the presence of an entity alone does not classify intent accurately - any of these intentions could occur with a product X - ‘i am thinking of getting X’ (transactional); ‘i like my new X’ (information sharing); and ‘what do you think about X’ (information seeking). My approach to automatic identification of intents relied on using ‘action patterns’ – pattern of words surrounding entity X. Using a set of seed ‘action patterns’ indicating intent, I developed a minimally supervised bootstrapping algorithm that learns new intent revealing patterns from an un-annotated corpus of 10K user posts from MySpace. Intent tendencies of new patterns are computed using semantic (using communicative functions of words from the LIWC dictionary) and distributional similarity with seed patterns.

As part of a targeted content delivery application [WI09], we found that the new learned patterns were effective in identifying monetizable posts, i.e., those with information seeking and transactional intents. We also found that users were 8 times more likely to click on ads that were generated from their monetizable footprints left on the network (in wall posts, forum messages) than those generated from their profile information (hobbies, activities etc.).