Methods and systems for social media-based profiling of entity location by associating entities and venues with geo-tagged short electronic messages

Patent metadata

Field	Value
Publication number	US-2016110381-A1
Application number	US-201414517791-A
Country	US
Kind code	A1
Filing date	Oct 17, 2014
Priority date	Oct 17, 2014
Publication date	Apr 21, 2016
Grant date	—

Abstract

A method includes: obtaining from a first social media source a new short unstructured electronic message with an associated geographic location and message content; identifying a first venue name and a first visit characteristic from the message content; accessing a database of venues, wherein the database includes for respective venues a venue name, a geographic location and one or more venue characteristics, wherein information in the database reflects information associated with the respective venues extracted from a plurality of social media posts, including a plurality of prior short unstructured electronic messages from the first social media source; determining whether the database includes a candidate venue that has a venue name and geographic location that respectively are substantially similar to the first venue name and the associated geographic location; when the candidate venue exists in the database, associating the new short unstructured electronic message with the candidate venue and perform updates.

First claim

What is claimed is:

1 . A method, comprising:
at a computer system with one or more processors and memory storing instructions for execution by the processor: obtaining from a first social media source a new short unstructured electronic message with an associated geographic location and message content; identifying a first venue name and a first visit characteristic from the message content; accessing a database of venues, wherein the database includes for respective venues a venue name, a geographic location and one or more venue characteristics, wherein information in the database reflects information associated with the respective venues extracted from a plurality of social media posts, including a plurality of prior short unstructured electronic messages from the first social media source; determining whether the database includes a candidate venue that has a venue name and geographic location that respectively are substantially similar to the first venue name and the associated geographic location; when the candidate venue exists in the database, associating the new short unstructured electronic message with the candidate venue; and when venue records in the database are associated with more than a threshold number of new short unstructured electronic messages, updating the one or more venue characteristics of the venue records based on the first visit characteristics of the associated new short unstructured electronic messages.

2 . The method of claim 1 , further comprising:
when the candidate venue does not exist in the database, adding a new venue record to the database based on the first venue name, the associated geographic location and the first characteristic.

3 . The method of claim 1 , wherein the first visit characteristic is at least one of a sentiment orientation or a group size.

4 . The method of claim 1 , wherein determining whether the database includes a candidate venue that has a venue geographic location that is substantially similar to the associated geographic location; includes:
determining whether distance between the venue geographic location and the associated geographic location is less than a predetermined distance.

5 . The method of claim 1 , wherein the database includes for a respective venue a number of check-ins, a number of unique visitors, and a core venue indicator, further comprising as a preliminary operation:
obtaining from a first information source a first plurality of short unstructured electronic messages, each having an associated first geographic location and message content, wherein the message content includes the first venue name and one or more visit characteristics; obtaining from a second information source a second plurality of venue locations, each having an associated second geographic location and second venue name that is substantially similar to the first venue name; determining for each venue location in the second plurality whether each respective short message in the first plurality has an associated first geographic location that is within a predefined distance of the second geographic location associated with the each venue location; in response to the determining, associating with a venue in the database respective short messages and venue locations whose associated first and second geographic locations are within the predefined distance; applying a clustering algorithm to the database to cluster the venues into venue groups and filter out outliers, wherein the outliers represent one or more venues in the database that have one or more aggregate characteristics that are substantially different from corresponding aggregate characteristics of other venues in the database; identifying for each venue group a core venue that has most number of check-ins in the venue group; and updating the core venue indicator for the core venue.

6 . The method of claim 5 , wherein updating the core venue record based on the first characteristics of the associated short unstructured electronic messages includes:
for a venue group in the venue groups:
tagging the associated short unstructured electronic messages with the core venue; and
updating the core venue record corresponding to the core venue based on the first characteristics of the associated short unstructured electronic messages.

7 . The method of claim 5 , further comprising:
assigning sentiment orientations to the message content that recites comments about of the venues, the sentiment orientations indicating whether the message content reflects a positive, neutral, or negative sentiment; classifying sentiment degree within a particular sentiment orientation; computing a sentiment score based on the sentiment orientations; and associating the sentiment score with the short unstructured electronic message.

8 . The method of claim 7 , further comprising:
for a venue group in the venue groups:
identifying the core venue of the venue group;
identifying the tagged short unstructured electronic messages associated with the core venue;
computing an overall sentiment of the core venue based on sentiment scores associated with the tagged short unstructured electronic messages; and
deriving a sentiment heatmap from the venue groups, the sentiment heatmap reflecting the overall sentiments towards each core venue and the venue name and the geographic location of each core venue.

9 . The method of claim 8 , wherein deriving the sentiment heatmap includes:
encoding an overall sentiment associated with a particular core venue using a distinctive visual characteristic, including one of: mark size, mark color and mark size and color.

10 . The method of claim 5 , further comprising:
determining whether a facial image is associated with the short unstructured electronic message; when the facial image exists:
detecting the number of faces in the facial image;
assigning the short unstructured electronic message to a size category based on the number of faces in the facial image; and
associating the size category with the short unstructured electronic message.

11 . The method of claim 10 , wherein the clustering algorithm is a density-based clustering algorithm.

12 . The method of claim 10 , further comprising:
for a venue group in the venue groups:
identifying a core venue of the venue group;
identifying the tagged short unstructured electronic messages associated with the core venue;
computing an average group size of the core venue based on size categories associated with the tagged short unstructured electronic messages; and
deriving a social group size heatmap from the venue groups, the social group size heatmap reflecting the average group size visiting each core venue and the venue name and the geographic location of each core venue.

13 . The method of claim 12 , wherein deriving the social group size heatmap includes:
encoding an average social group size associated with a particular core venue using a distinctive visual characteristic, including one of: mark size, mark color and mark size and color.

14 . The method of claim 5 , wherein the one or more aggregate characteristics include one or more of: a minimum number of visitors to the venue or a minimum number of short messages associated with the venue.

15 . The method of claim 1 , wherein updating the one or more venue characteristics includes:
accessing the database of venues, wherein the database includes for respective venues a venue name, a geographic location and one or more venue characteristics, wherein information in the database reflects information associated with the

Assignees

• Fuji Xerox Co Ltd

Inventors

• Chen Francine
• Joshi Dhiraj

Classifications

• G06Q10/40

  Business processes related to social networking or social networking services · CPC title

• G06F16/9537

  Spatial or temporal dependent retrieval, e.g. spatiotemporal queries · CPC title

• G06F16/29 Primary

  Geographical information databases · CPC title

• G06F17/3087

  Physics · mapped topic

• G06F17/30241 Primary

  Physics · mapped topic