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Attitudinal Filter for Social Media Posts

IP.com Disclosure Number: IPCOM000218944D
Publication Date: 2012-Jun-12
Document File: 1 page(s) / 18K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a system to assist users in filtering unwanted content or posts from their social media newsfeeds based on attitudes or sentiments. The system leverages a standardized and/or customizable taxonomy of words with an associated attitudinal value to apply a client-side filter option for any social media application.

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Attitudinal Filter for Social Media Posts

Social media applications provide a massive amount of content to any user. There are filters and customizable options for opting in and out of certain feeds at a content provider level, but many filters available to sort at a client side across multiple content sources are based on content attribute rather than user attribute, such as attitude. Currently, a user can filter out certain friends from their social network feed, or they can filter out types of content, such as photos or game notifications.

There are no designs that allow client-side interaction with data related to attitudes or sentiments for filter selections based on user preference.

The invention is for a means of leveraging a standardized and/or customizable taxonomy of words with an attitudinal value applied to apply a client-side filter option for any social media application. An example taxonomy is: http://www.liwc.net/. The filter allows the user to declare that they do not want to view any number of attitudinal sentiments (e.g. "unpleasant") in posts or content.

The system also takes into consideration what is "unpleasant" to one user might be "pleasant" to another user based upon their views and likes or dislikes. This data may be gleaned from the user's previous interactions in the social network and external systems. Consequently, the system also considers the viewpoints and characteristics of a user to determine what should be filtered when given...