Methods and apparatus to estimate demographics of an audience of a media event using social media message sentiment

Patent metadata

Field	Value
Publication number	US-2016189181-A1
Application number	US-201414584436-A
Country	US
Kind code	A1
Filing date	Dec 29, 2014
Priority date	Dec 29, 2014
Publication date	Jun 30, 2016
Grant date	—

Abstract

Methods, apparatus, systems and articles of manufacture to estimate demographics of an audience of a media event using social media message sentiment are disclosed. An example method includes calculating a sentiment score for a media-exposure social media message received from a social media server. The media-exposure social media message is identified based on a media keyword. Demographic information associated with users who viewed the media-exposure social media message is retrieved. An estimated impact on a size of a demographic segment of viewers is calculated using the sentiment score and the demographic information.

First claim

What is claimed is:

1 . A method to estimate demographics for an audience of a media event, the method comprising:
calculating, with a processor, a sentiment score for a media-exposure social media message received from a social media server, the media-exposure social media message identified based on a media keyword; retrieving demographic information associated with users who viewed the media-exposure social media message; and calculating an estimated impact on a size of a demographic segment of viewers using the sentiment score and the demographic information.

2 . The method as defined in claim 1 , wherein calculating the sentiment score further comprises:
parsing a text of the media-exposure social media message to identify a keyword; associating the keyword with a value; and summing the value for a plurality of keywords identified in the text of the media-exposure social media message.

3 . The method as defined in claim 1 , further comprising identifying the media-exposure social media message by:
identifying a reference to the media event in a text of the media-exposure social media message; and determining whether a characteristic of the media-exposure social media message satisfies a rule associated with the media event.

4 . The method as defined in claim 3 , wherein the rule associated with the media event is a broadcast time of the media event.

5 . The method as defined in claim 3 , further comprising calculating the sentiment score for the media-exposure social media message in response to determining that the characteristic of the media-exposure social media message satisfies the rule associated with the media event.

6 . The method as defined in claim 1 , wherein determining the demographics associated with users of social media exposed to the media-exposure social media message comprises:
identifying an impression associated with the social media message, the impression corresponding with exposure to the social media message; identifying a user identifier associated with the impression; and determining demographics associated with the user identifier.

7 . The method as defined in claim 1 , wherein the sentiment score is a first sentiment score, the media-exposure social media message is a first media-exposure social media message, the estimated impact is a first estimated impact, and further comprising:
calculating a sentiment score associated with a second media-exposure social media message; and calculating an second estimated impact on the size of the demographic segment of viewers using the second sentiment score and the demographic information; and calculating a total estimated impact on the size of the demographic segment of viewers using the first estimated impact and the second estimated impact.

8 . An apparatus to estimate demographics for an audience, the apparatus comprising:
a query transmitter to transmit, to a social media server, a query requesting a media-exposure social media message and demographic information associated with impressions of the media-exposure social media message, the media-exposure social media message associated with media; a sentiment estimator to calculate a sentiment score for the media-exposure social media message; and an audience demographic estimator to calculate an estimated impact on a size of a demographic segment based on the sentiment score and the demographic information.

9 . The apparatus as defined in claim 8 , wherein the sentiment estimator is to parse a text of the media-exposure social media message to identify a presence of a sentiment keyword within the text of the media-exposure social media message.

10 . The apparatus as defined in claim 8 , further comprising a query generator to generate the query based on a media profile identifying when the media is presented.

11 . The apparatus as defined in claim 8 , further comprising a query generator to generate the query based on a media keyword associated with the media.

12 . The apparatus as defined in claim 8 , wherein the sentiment score is a first sentiment score, the media-exposure social media message is a first media-exposure social media message, the demographic information is a first demographic information, the audience demographic estimator is further to calculate the estimated impact on the size of the demographic segment based on a second sentiment score associated with a second media-exposure social media message and second demographic information associated with the second media-exposure social media message.

13 . The apparatus as defined in claim 8 , further comprising a reporter to generate a report indicative of the size of the demographic segment.

14 . A tangible machine readable storage medium comprising instructions which, when executed, cause a machine to at least:
calculate a sentiment score for a media-exposure social media message received from a social media server, the media-exposure social media message identified based on a media keyword; retrieve demographic information associated with users who viewed the media-exposure social media message; and calculate an estimated impact on a size of a demographic segment of viewers using the sentiment score and the demographic information.

15 . The machine readable storage medium as defined in claim 14 , further comprising instructions which, when executed, cause the machine to at least:
parse a text of the media-exposure social media message to identify a keyword; associate the keyword with a value; and sum the value for a plurality of keywords identified in the text of the media-exposure social media message.

16 . The machine readable storage medium as defined in claim 14 , further comprising instructions which, when executed, cause the machine to at least:
identify a reference to the media event in a text of the media-exposure social media message; and determine whether a characteristic of the media-exposure social media message satisfies a rule associated with the media event.

17 . The machine readable storage medium as defined in claim 16 , wherein the rule associated with the media event is a broadcast time of the media event.

18 . The machine readable storage medium as defined in claim 16 , further comprising instructions which, when executed, cause the machine to calculate the sentiment score for the media-exposure social media message in response to determining that the characteristic of the media-exposure social media message satisfies the rule associated with the media event.

19 . The machine readable storage medium as defined in claim 14 , further comprising instructions which, when executed, cause the machine to at least:
identify an impression associated with the social media message, the impression corresponding with exposure to the social media message; identify a user identifier associated with the impression; and determine demographics associated with the user identifier.

20 . The machine readable storage medium as defined in claim 14 , wherein the sentiment score is a first sentiment score, the media-exposure social media message is a first media-exposure social media message, the estimated impact is a first estimated impact, and further comprising instructions which, when executed, cause the machine to at least:
calculate a sentiment score associated with a second media-exposure social media message; and calculate an second estimated impact on the size of the demographic segment of viewers using the second sentiment score and the demo

Assignees

• Nielsen Co Us Llc

Inventors

• Mcclave Caroline Hepworth
• Anderson Sarah Elizabeth
• Terrazas Alejandro
• Sheppard Michael Richard
• Reid Matt

Classifications

• G06Q10/40

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

• G06Q30/0204 Primary

  Market segmentation · CPC title

• G06Q50/01

  Physics · mapped topic