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Searching for best places (geographical) for offered service, bilboard, marketing campain, etc.) based on social media analysis

IP.com Disclosure Number: IPCOM000242953D
Publication Date: 2015-Sep-02
Document File: 1 page(s) / 34K

Publishing Venue

The IP.com Prior Art Database

Abstract

Billboard, and in general, any physical advertisement placement may be a hard task. Obviously company that is advertising must take under consideration distance to some institutions (for example place toys advertisements somewhere near schools) to reach people they want to target. Disclosed is idea to choose location of physical advertisements based on social media data (geolocation, user description, post content, expressed sentiments, discussed topics etc)

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Searching for best places ( , campain,

) ((geographical

geographical )

,

for offered service

for offered service ,

bilboard

bilboard, ,

marketing

marketing

etc.) based on social media analysis

based on social media analysis

System, that would support placing physical advertisements, in order to simplify advertising and make it more effective.

System would download social media data, analyze it in order to assess which users belong to the target group and calculate density of people from the target group on a map.

social media - twitter, facebook, etc.
social media data - any data with attached location, i.e. posts, comments, check -ins etc. plus user info.
specified location - any geographically bounded area, for example some city

Possible use case:


Let's assume that company XYZ wants to place a billboard that advertises it's new product in New York City. Product that is being advertised is mostly designed for young educated people (that is target group).

User defines potential billboard locations

System downloads social media posts from specific location (in this case, New York), and user info available on social media. Data may be gathered for some period of time (few days, weeks, maybe months).

System categorizes users that wrote posts based on posts content, user description, friends, etc. System then identifies which users belong to the target group.

System calculates number of people from the target group nearby (ex 500 meters) for each possible billboard lo...