Item request has been placed!
×
Item request cannot be made.
×
Processing Request
Social intelligence architecture using social media message queues
Item request has been placed!
×
Item request cannot be made.
×
Processing Request
- Publication Date:October 31, 2023
- معلومة اضافية
- Patent Number: 11803,557
- Appl. No: 17/381275
- Application Filed: July 21, 2021
- نبذة مختصرة : A social intelligence system is presented that streams information from a source, queues the streamed information, analyzes/scores the queued data, and stores the analyzed/scored data in an analysis database. The analyzed/scored data can then be retrieved from the database for post-processing and stored in a client specific database for further reporting. By streaming the data into various message queues and scoring the data before storing in the analysis database, large volumes of data can be efficiently processed and analyzed for a particular person and/or entity.
- Inventors: Nasdaq, Inc. (New York, NY, US)
- Assignees: NASDAQ, INC. (New York, NY, US)
- Claim: 1. A system, comprising: a processor; and a memory configured to store computer readable instructions that, when executed by the processor, cause the system to: receive social media data streamed using streaming services, wherein the social media data is associated with social media data sources, and the social media data is continuously broadcast using the streaming services; queue the received social media data into a plurality of message queues, wherein the social media data is queued into the plurality of message queues as the social media data is continuously broadcast using the streaming services; retrieve the social media data from the plurality of message queues; analyze the social media data using analysis services of the system; assign a value to each of the analyzed social media data, wherein the value represents a score and polarity for each of the analyzed social media data, and the value is assigned based on a viewpoint of an entity for which the sentiment analysis is being performed; generate a resultant sentiment based on the value assigned to each of the analyzed social media data; store the social media data and the associated resultant sentiment into analysis databases of the system by moving the social media data and the associated resultant sentiment from the analysis services of the system to the analysis databases of the system; and generate a user interface for display, wherein the user interface displays information associated with the stored social media data and the stored associated resultant sentiment.
- Claim: 2. The system of claim 1 , wherein the system is further caused to move the social media data and the associated resultant sentiment from the analysis databases to client specific databases of the system.
- Claim: 3. The system of claim 1 , wherein the system is further caused to move the social media data and the associated resultant sentiment from the analysis databases to historical databases of the system.
- Claim: 4. The system of claim 3 , wherein the system is further caused to: determine a relevance of the analyzed social media data; and determine whether to store the social media data and the associated resultant sentiment into the analysis databases or the historical databases based on the relevance.
- Claim: 5. The system of claim 1 , wherein the social media data is analyzed using the analysis services after retrieving the social media data from the plurality of message queues and prior to storing the social media data and the associated resultant sentiment into the analysis databases of the system.
- Claim: 6. The system of claim 1 , wherein the value includes a numerical value, and the resultant sentiment is generated based on a sum of the numerical value assigned to each of the analyzed social media data.
- Claim: 7. The system of claim 1 , wherein a pipeline is created from the social media data sources to the analysis databases of the system by queuing the social media data, analyzing the social media data, assigning the value to each of the social media data, and storing the social media data and the associated resultant sentiment.
- Claim: 8. The system of claim 1 , wherein the analysis services are configured to assign the value differently depending upon whether the analyzed social media data includes sentiment associated with an entity or sentiment associated with a competitor of the entity for which the sentiment analysis is being performed.
- Claim: 9. A method for analyzing social media data, comprising: at a system having at least a processor and a memory: receiving social media data streamed using streaming services, wherein the social media data is associated with social media data sources, and the social media data is continuously broadcast using the streaming services; queueing the received social media data into a plurality of message queues, wherein the social media data is queued into the plurality of message queues as the social media data is continuously broadcast using the streaming services; retrieving the social media data from the plurality of message queues; analyzing the social media data using analysis services of the system; assigning a value to each of the analyzed social media data, wherein the value represents a score and polarity for each of the analyzed social media data, and the value is assigned based on a viewpoint of an entity for which the sentiment analysis is being performed; generating a resultant sentiment based on the value assigned to each of the analyzed social media data; and storing the social media data and the associated resultant sentiment into analysis databases of the system.
- Claim: 10. The method of claim 9 , further comprising moving the social media data and the associated resultant sentiment from the analysis databases to historical databases of the system.
- Claim: 11. The method of claim 10 , further comprising: determining a relevance of the analyzed social media data; and determining whether to store the social media data and the associated resultant sentiment into the analysis databases or the historical databases based on the relevance.
- Claim: 12. The method of claim 10 , wherein the value includes a numerical value, and the resultant sentiment is generated based on a sum of the numerical value assigned to each of the analyzed social media data.
- Claim: 13. The method of claim 10 , wherein the analysis services are configured to assign the value differently depending upon whether the analyzed social media data includes sentiment associated with an entity or sentiment associated with a competitor of the entity for which the sentiment analysis is being performed.
- Claim: 14. A non-transitory computer readable storage medium having computer readable instructions stored therein which, when executed by a processor of a system, cause the system to provide execution comprising: receiving social media data streamed using streaming services, wherein the social media data is associated with social media data sources, and the social media data is continuously broadcast using the streaming services; queueing the received social media data into a plurality of message queues, wherein the social media data is queued into the plurality of message queues as the social media data is continuously broadcast using the streaming services; retrieving the social media data from the plurality of message queues; analyzing the social media data using analysis services of the system; assigning a value to each of the analyzed social media data, wherein the value represents a score and polarity for each of the analyzed social media data, and the value is assigned based on a viewpoint of an entity for which the sentiment analysis is being performed; generating a resultant sentiment based on the value assigned to each of the analyzed social media data; and storing the social media data and the associated resultant sentiment into analysis databases of the system.
- Claim: 15. The non-transitory computer readable storage medium of claim 14 , wherein the system is further caused to provide execution comprising moving the social media data and the associated resultant sentiment from the analysis databases to historical databases of the system.
- Claim: 16. The non-transitory computer readable storage medium of claim 15 , wherein the system is further caused to provide execution comprising: determining a relevance of the analyzed social media data; and determining whether to store the social media data and the associated resultant sentiment into the analysis databases or the historical databases based on the relevance.
- Claim: 17. The non-transitory computer readable storage medium of claim 14 , wherein the value includes a numerical value, and the resultant sentiment is generated based on a sum of the numerical value assigned to each of the analyzed social media data.
- Claim: 18. The system of claim 1 , wherein the system is further caused to move portions of the social media data and the associated resultant sentiment from the analysis databases to historical databases of the system, and the portions of the social media data and the associated resultant sentiment stored in the historical databases from the system are excluded from the information associated with the stored social media data and the stored associated resultant sentiment displayed by the user interface.
- Claim: 19. The system of claim 2 , wherein when the social media data and the associated resultant sentiment is not intended to be move to the client specific databases, the system is further caused to move the social media data and the associated resultant sentiment from the analysis databases to historical databases of the system.
- Claim: 20. The system of claim 1 , wherein the user interface is generated using one or more web user interface services.
- Patent References Cited: 6728707 April 2004 Wakefield et al.
6732097 May 2004 Wakefield et al.
6732098 May 2004 Wakefield et al.
6738765 May 2004 Wakefield et al.
6741988 May 2004 Wakefield et al.
7171349 January 2007 Wakefield et al.
7428528 September 2008 Ferrari et al.
7472427 December 2008 Shimojima et al.
7600017 October 2009 Holtzman et al.
7660783 February 2010 Reed
7720835 May 2010 Ward et al.
7792841 September 2010 McAllister et al.
7814043 October 2010 Uchino
7849048 December 2010 Langseth et al.
7865394 January 2011 Calloway et al.
7877345 January 2011 Nigam et al.
7930302 April 2011 Bandaru et al.
7966241 June 2011 Nosegbe
7974983 July 2011 Goeldi
7984428 July 2011 Seymour
8010524 August 2011 Chen et al.
8225413 July 2012 De et al.
20020083039 June 2002 Ferrari et al.
20030101166 May 2003 Uchino et al.
20040036716 February 2004 Jordahl
20040167870 August 2004 Wakefield et al.
20040167883 August 2004 Wakefield et al.
20040167884 August 2004 Wakefield et al.
20040167885 August 2004 Wakefield et al.
20040167886 August 2004 Wakefield et al.
20040167887 August 2004 Wakefield et al.
20040167907 August 2004 Wakefield et al.
20040167908 August 2004 Wakefield et al.
20040167909 August 2004 Wakefield et al.
20040167910 August 2004 Wakefield et al.
20040167911 August 2004 Wakefield et al.
20040215634 October 2004 Wakefield et al.
20050027629 February 2005 De Breed et al.
20050038781 February 2005 Ferrari et al.
20050108256 May 2005 Wakefield et al.
20060053104 March 2006 Ferrari et al.
20060242040 October 2006 Rader
20070011183 January 2007 Langseth et al.
20070083505 April 2007 Ferrari et al.
20070100875 May 2007 Chi et al.
20080072256 March 2008 Boicey et al.
20080134100 June 2008 Ferrari et al.
20080154698 June 2008 Flake et al.
20080154883 June 2008 Chowdhury et al.
20080228695 September 2008 Sifry et al.
20080256093 October 2008 Amitay et al.
20090106697 April 2009 Ward et al.
20090119156 May 2009 Dulepet
20090119157 May 2009 Dulepet
20090119173 May 2009 Parsons et al.
20090125482 May 2009 Peregrine et al.
20090164266 June 2009 Lakhani et al.
20090319342 December 2009 Shilman et al.
20090319518 December 2009 Koudas et al.
20100049590 February 2010 Anshul
20100070485 March 2010 Parsons et al.
20100082695 April 2010 Hardt
20100088313 April 2010 Hoffman et al.
20100114899 May 2010 Guha et al.
20100119053 May 2010 Goeldi
20100121707 May 2010 Goeldi
20100169159 July 2010 Rose et al.
20100241620 September 2010 Manister et al.
20100275128 October 2010 Yu et al.
20100325107 October 2010 Ward et al.
20100287136 November 2010 Fortuna, Jr. et al.
20100332465 December 2010 Janssens et al.
20110029926 February 2011 Hao et al.
20110047035 February 2011 Gidwani et al.
20110078157 March 2011 Sun et al.
20110078584 March 2011 Winterstein et al.
20110106589 May 2011 Blomberg et al.
20110106807 May 2011 Srihari et al.
20110144971 June 2011 Danielson
20110145219 June 2011 Cierniak et al.
20110191372 August 2011 Kaushansky et al.
20110246463 October 2011 Carson, Jr. et al.
20110282860 November 2011 Baarman et al.
20120047219 February 2012 Feng et al.
20120254333 October 2012 Chandramouli et al.
20130006685 January 2013 Kelkar
20130073480 March 2013 Sastri
20130103667 April 2013 Minh
20130110583 May 2013 Ormont et al.
20130138428 May 2013 Chandramouli et al.
2302533 March 2011
2412196 September 2005
1072114 November 2009
WO 0139065 May 2001
WO 0246997 June 2002
WO 02097671 December 2002
WO 03027901 April 2003
WO 03027902 April 2003
WO 03054746 July 2003
WO 2004053645 June 2004
WO 2005026992 March 2005
WO 2005076175 August 2005
WO 2006039566 April 2006
WO 2007/002839 January 2007
WO 2007015990 February 2007
WO 2007058863 May 2007
WO 2007101263 September 2007
WO 2008039542 April 2008
WO 2008067554 June 2008
WO 2009003050 December 2008
WO 2009023865 February 2009
WO 2009105277 August 2009
WO 2009155375 December 2009
WO 2010065199 June 2010 - Other References: International Search Report for PCT/SE2013/050465 dated Feb. 5, 2014. cited by applicant
Written Opinion of the International Searching Authority for PCT/SE2013/050465 dated Feb. 5, 2014. cited by applicant
Bifet et al., “MOA-TweetReader: Real-Time Analysis in Twitter Streaming Data” Discovery Science, Springer Berlin Heidelberg, 2011, vol. 6926, pp. 46-60. cited by applicant
Office Action in U.S. Appl. No. 13/465,307 dated Jul. 2, 2013. cited by applicant
Office Action in U.S. Appl. No. 13/465,307 dated Apr. 4, 2014. cited by applicant
Office Action in U.S. Appl. No. 13/465,307 dated Apr. 1, 2015. cited by applicant
Office Action in U.S. Appl. No. 13/465,307 dated Sep. 30, 2015. cited by applicant
Warren Sack, On The Computation of Point of View, 1994, MIT, AAAI-94 proceedings, p. 488 (Year: 1994). cited by applicant - Primary Examiner: Kim, Taelor
- Attorney, Agent or Firm: Nixon & Vanderhye, PC
- الرقم المعرف: edspgr.11803557
- Patent Number:
حقوق النشر© 2024، دائرة الثقافة والسياحة جميع الحقوق محفوظة Powered By EBSCO Stacks 3.3.0 [353] | Staff Login
حقوق النشر © دائرة الثقافة والسياحة، جميع الحقوق محفوظة
No Comments.