Method and apparatus of analyzing social network data to identify a financial market trend
In general, the present disclosure includes a system, method and architecture for use in analyzing content of a social network data to identify a financial market trend, e.g., a trend associated with a financial market instrument.
1. A method comprising:
receiving, by a computing device of an online financial information provider, a corpus of social media posts of a number of users of at least one social media system, each social media post, of the corpus, containing a reference to a financial market entity and occurring in either a first time interval or a second time interval; and
identifying, by the computing device, a percentage change in number of social media references using the corpus of social media posts, the identifying comprising:
determining, by the computing device, a first number of occurrences of the reference to the financial market entity in a first set of social media posts, from the corpus, occurring in the first time interval;
determining, by the computing device, a second number of occurrences of the reference to the financial market entity in a second set of social media posts, from the corpus, occurring in the second time interval; and
determining, by the computing device, the percentage change in number of social media references to the financial market entity using the determined first and second numbers of occurrences of the reference to the financial market entity; and
displaying, via the computing device, the determined percentage change in a display of the online financial information provider at a number of client computing devices, the displaying comprising transmitting the determined percentage change via an electronic communications network to the number of client computing devices.
2. The method of claim 1 , further comprising:
providing, by the computing device and to the number of client computing devices, the determined percentage change in number of social media references to the financial market entity as a trend associated with the financial market entity.
3. The method of claim 1 , further comprising:
determining, by the computing device, a respective percentage change in number of social media references for each of a number of other financial market entities; and
selecting, by the computing device, the determined percentage change in number of social media references to the financial market entity as the determined percentage change to provide to the number of client computing devices rather than the respective percentage change in number of social media references for each of the number of other financial market entities, the selecting comprising comparing the determined percentage change with the respective percentage change in number of social media references determined for each of the number of other financial market entities.
4. The method of claim 3 , further comprising:
determining, by the computing device, a sentiment associated with the financial market entity using one or more social media posts from the corpus; and
using selecting, by the computing device, the determined percentage change to provide to the number of client computing devices using the determined sentiment.
5. The method of claim 1 , the first number of occurrences representing a volume of occurrences of the reference to the financial market entity in the first set of social media posts and the second number of occurrences representing a volume of occurrences of the reference to the financial market entity in the second set of social media posts.
6. The method of claim 1 , the percentage change indicating whether occurrences of the social media references to the financial market entity are trending up, down or are neutral.
7. The method of claim 6 , further comprising:
determining, by the computing device, a sentiment associated with the financial market entity using one or more social media posts from the corpus; and
determining, by the computing device, whether the social media references to the financial market entity are trending up, down or are neutral using the determined sentiment.
8. The method of claim 1 ,
determining, by the computing device, the first number of occurrences of the reference to the financial market entity in the first set of social media posts further comprising analyzing content of each social media post in the first set of social media posts; and
determining, by the computing device, the second number of occurrences of the reference to the financial market entity in the second set of social media posts further comprising analyzing content of each social media post in the second set of social media posts.
9. A non-transitory computer-readable storage medium tangibly storing computer-executable instructions that when executed by a processor of an online financial information provider causes the processor of the online financial information provider to perform steps comprising:
receiving a corpus of social media posts of a number of users of at least one social media system, each social media post, of the corpus, containing a reference to a financial market entity and occurring in either a first time interval or a second time interval; and
identifying a percentage change in number of social media references using the corpus of social media posts, the identifying comprising:
determining a first number of occurrences of the reference to the financial market entity in a first set of social media posts, from the corpus, occurring in the first time interval;
determining a second number of occurrences of the reference to the financial market entity in a second set of social media posts, from the corpus, occurring in the second time interval; and
determining the percentage change in number of social media references to the financial market entity using the determined first and second numbers of occurrences of the reference to the financial market entity; and
displaying the determined percentage change in a display of the online financial information provider at a number of client computing devices, the displaying comprising transmitting the determined percentage change via an electronic communications network to the number of client computing devices.
10. The non-transitory computer-readable storage medium of claim 9 tangibly storing computer-executable instructions that when executed by the processor of the online financial information provider causes the processor to further perform:
providing, to the number of client computing devices, the determined percentage change in number of social media references to the financial market entity as a trend associated with the financial market entity.
11. The non-transitory computer-readable storage medium of claim 9 tangibly storing computer-executable instructions that when executed by the processor of the online financial information provider causes the processor to further perform:
determining a respective percentage change in number of social media references for each of a number of other financial market entities; and
selecting the determined percentage change in number of social media references to the financial market entity as the determined percentage change to provide to the number of client computing devices rather than the respective percentage change in number of social media references for each of the number of other financial market entities, the selecting comprising comparing the determined percentage change with the respective percentage change in number of social media references determined for each of the number of other financial market entities.
12. The non-transitory computer-readable storage medium of claim 11 tangibly storing computer-executable instructions that when executed by the processor of the online financial information provider causes the processor to further perform:
determining a sentiment associated with the financial market entity using one or more social media posts from the corpus; and
selecting the determined percentage change to provide to the number of client computing devices using the determined sentiment.
13. The non-transitory computer-readable storage medium of claim 9 , the first number of occurrences representing a volume of occurrences of the reference to the financial market entity in the first set of social media posts and the second number of occurrences representing a volume of occurrences of the reference to the financial market entity in the second set of social media posts.
14. The non-transitory computer-readable storage medium of claim 9 , the percentage change indicating whether occurrences of the social media references to the financial market entity are trending up, down or are neutral.
15. The non-transitory computer-readable storage medium of claim 14 tangibly storing computer-executable instructions that when executed by the processor of the online financial information provider causes the processor to further perform:
determining a sentiment associated with the financial market entity using one or more social media posts from the corpus; and
determining whether the social media references to the financial market entity are trending up, down or are neutral using the determined sentiment.
16. The non-transitory computer-readable storage medium of claim 9 tangibly storing computer-executable instructions that when executed by the processor of the online financial information provider causes the processor to further perform:
determining the first number of occurrences of the reference to the financial market entity in the first set of social media posts further comprising analyzing content of each social media post in the first set of social media posts; and
determining the second number of occurrences of the reference to the financial market entity in the second set of social media posts further comprising analyzing content of each social media post in the second set of social media posts.
17. A computing device of an online financial information provider comprising:
a processor;
a non-transitory storage medium tangibly storing thereon program logic that when executed by the processor causes the processor to perform a steps comprising:
receiving a corpus of social media posts of a number of users of at least one social media system, each social media post, of the corpus, containing a reference to a financial market entity and occurring in either a first time interval or a second time interval; and
identifying a percentage change in number of social media references using the corpus of social media posts, the identifying comprising:
determining a first number of occurrences of the reference to the financial market entity in a first set of social media posts, from the corpus, occurring in the first time interval;
determining a second number of occurrences of the reference to the financial market entity in a second set of social media posts, from the corpus, occurring in the second time interval; and
determining the percentage change in number of social media references to the financial market entity using the determined first and second numbers of occurrences of the reference to the financial market entity; and
displaying the determined percentage change in a display of the online financial information provider at a number of client computing devices, the displaying comprising transmitting the determined percentage change via an electronic communications network to the number of client computing devices.