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Method for Using Text Analytics to Determine a User's Preferences and Affinities by Analyzing Social Media Posts and Comments

IP.com Disclosure Number: IPCOM000243070D
Publication Date: 2015-Sep-11
Document File: 2 page(s) / 135K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a method and system of using text analytics to determine a user's preferences and affinities through analysis of the users social media posts and comments to assign confidence level from positive and negative feedback. Gaining insight to the users preferences and affinities can then be used for the purposes of target marketing and ultimately drive sales of goods and services.

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Method for Using Text Analytics to Determine a User's Preferences and Affinities by Analyzing Social Media Posts and Comments

Disclosed is a method and system of using text analytics to determine a user's preferences and affinities through analysis of the user's social media posts and comments to assign confidence level from positive and negative feedback. Gaining insight to the user's preferences and affinities can then be used for the purposes of target marketing and ultimately drive sales of goods and services. A key aspect in the

disclosed algorithm is to determine user sentiment that is considered positive, and sentiment that is negative.

Social media such as Facebook includes the ability for users to post comments, photographs, video, etc. and for members of the social network with appropriate access to provide feedback on the content posted. The common types of social network feedback include likes or dislike, star rating (1-5), and comments.

Advertiser or business interest in driving online commerce have a strong motive in

understanding a user's sentiment about a wide variety of topics to get a more accurate assessment of a person's interests or likes for targeted advertising to influence opinion or drive commerce.

Provided is a method and system of using text analytics to determine a user's preferences and affinities through analysis of the user's social media posts and comments to assign confidence level from positive and negative feedback. Gaining insight to the user's preferences and affinities can then be used for the purposes of target marketing and ultimately drive sales of goods and services.

The components and implementation are as follows:

Components:

Social content (ie. Facebook, Twitter, Google, etc.)

Cognitive system with invention software

Implementation Steps:

Social media posting analysis of user posting.


1.

Perform sentiment analysis on each posting


1.

Perfor...