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Aggregation and Analysis of Multiple Social Media Provider Content for Targeted Advertising

IP.com Disclosure Number: IPCOM000241625D
Publication Date: 2015-May-18
Document File: 3 page(s) / 33K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed are a method and system for real time content aggregation of a user’s and associated friends’ and family posts from across multiple social media data sources and content types, as well as the collection of associated sentiment across device types. The collection and analysis of this aggregated social sentiment is consumed by the social media provider in order to develop target marketing for advertisers.

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Aggregation and Analysis of Multiple Social Media Provider Content for Targeted Advertising

Technology users consume content from many sources in real time using the same or different devices. For example, a user may use a tablet, a laptop, and a mobile device to view and contribute content on a social media site, read text messages, shop online, use search engines, and interact with other service providers. Systems do not enable various data sources from the sites to share content.

A method or system is needed to aggregate content across data sources and types in order to better understand users' behavior across applications, sites, and content. A subsequent analysis can be leveraged for targeted advertising or marketing of goods and services.

Existing solutions track a user's behavior within a given social media site or web site and recommend or cross-sell products. Some implementations aggregate content as well. The proposed solution builds upon existing systems and extends the approach to the aggregation of content across providers for a given user, friends, and family, and across device types.

The novel contribution is a method and system of real time aggregation of content across multiple social media content provider data sources and content types (e.g., text, images, etc.) for users, friends, and family posts. In addition, the method and system collect sentiment across device types for analysis and correlation of behavior across content. The collection and analysis of this data enables the development of effective targeted advertising across different social networks and other content providers.

Understanding specific user behavior across social media and devices allows the advertisers a unique and more effective ability to perform target marketing across the different social media types. For example, a user might most frequently use Social Media Site A, but sentiment learned from Social Media Site B reveals more about the person's interests. This information can be used by advertiser to perform targeted marketing through social media sites.

Software installed in user's device(s) gathers the user's content consumption and, with user permission, analyzes it. The software connects to all of the user's devices (e.g., tablet, smart phone, laptop computer, etc.) and accordingly aggregates the contents from various sources. The software has the option to aggregate data from multiple predefined users (e.g., family members, network of friends, etc.). The system aggregates data from various sources, accordingly identifies the user's or group of users' preferences, and then allows the delivery of an appropriate advertisement.

The core components and prerequisites for implementing the system and method include:


 Social media


- User posts and sentiment

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    - Friends and family posts and sentiment
 Device software


- Component software is installed on the device (i.e. mobile, tablet, laptop, etc.) to track content consu...