Sentiment trent visualization relating to an event occuring in a particular geographic region

1. A method of determining sentiment trend visualization for localized events, the method being implemented on a system comprising a physical processor executing machine readable instructions, comprising:

identifying, based on disseminated information from a first geographic region, an event occurring in the first geographic region, wherein the disseminated information from the first geographic region includes public commentary from the first geographic region;

identifying a set of attributes that are related to the event;

extracting a set of sentiment words relating to the identified event from the disseminated information, wherein the extracted set of sentiment words are in a local language of the first geographic region; and

causing display, for a first attribute of the identified set of attributes, of a sentiment trend visualization that depicts a trend of determined sentiments for the first attribute, wherein the determined sentiments are based on the set of sentiment words for the first attribute.

2. The method of claim 1 , wherein identifying the set of attributes comprises:

determining a plurality of candidate attributes from the disseminated information;

identifying a subset of the plurality of candidate attributes as the set of attributes according to a set of selection criteria;

for each attribute of the set of attributes, associating the attribute with a subset of sentiment words from the extracted set of sentiment words.

3. The method of claim 1 , wherein the sentiment trend visualization depicts the trend of determined sentiments for the first attribute over a time period.

4. The method of claim 3 , further comprising:

presenting for display a list of the identified set of attributes;

receiving selection of a second attribute of the identified set of attributes, where the second attribute is different from the first attribute; and

changing the sentiment trend visualization to depict a second trend of determined sentiments of the second attribute over time.

5. The method of claim 1 , wherein the disseminated information includes a set of data records, the method further comprising:

accessing a set of sentiment scores associated with the first attribute, where each sentiment score of the set of the sentiment scores expresses a sentiment associated with the first attribute of a respective data record of the set of data records at a respective time;

aggregating a subset of sentiment scores of the set of sentiment scores within each time interval of a sequence of time intervals;

computing, for a first time interval of the sequence of time intervals, a first aggregate score of a first subset of sentiment scores associated with the first time interval;

wherein the sentiment trend visualization of the particular attribute comprises a graph of the first aggregate score.

6. The method of claim 1 , wherein the trend of depicted sentiments comprises a set of indicators associated with the identified set of attributes, the method

generating, for the first attribute, an indicator that comprises a set of connected cells, where each cell of the set of connected cells indicates a corresponding sentiment score related to the first attribute.

7. The method of claim 6 , wherein each cell in the set of connected cells is associated with a corresponding data record in a set of data records determined from the disseminated information.

8. The method of claim 7 , wherein the set of cells are ordered based on a set of characteristics related to the corresponding set of sentiment scores associated with the set of cells.

9. The method of claim 8 , wherein the set of characteristics includes positiveness of the sentiment scores.

10. The method of claim 6 , wherein each cell in the set of connected cells may be associated with visual indicators that indicate information about the corresponding sentiment score, the visual indicators including different colors corresponding to respective different sentiment scores.

11. A system comprising:

a physical processor that executes machine readable instructions that cause the system to:

identify, based on disseminated information from a first geographic region, an event occurring in the first geographic region, wherein the disseminated information from the first geographic region includes public commentary from the first geographic region;

determine a set of attributes related to the event;

extract a set of sentiment words relating to the identified event from the disseminated information, where the extracted set of sentiment words are in a local language of the first geographic region;

associate, for each attribute of the set of attributes, a sentiment from the set of sentiment words; and

cause display of a sentiment trend visualization that depicts a trend of determined sentiments for the first attribute, wherein the determined sentiments are based on the set of sentiment words for the first attribute.

12. The system of claim 11 , wherein the sentiment trend visualization comprises a set of indicators associated with the identified set of attributes, and wherein the physical processor executes machine readable instructions to:

generate, for the first attribute, an indicator that comprises a set of connected cells, where each cell of the set of connected cells indicates a corresponding sentiment score related to the first attribute.

13. The system of claim 12 , wherein each cell in the set of connected cells is associated with a corresponding data record in a set of data records determined from the disseminated information, and wherein the set of cells are ordered based on a set of characteristics related to the corresponding set of sentiment scores associated with the set of cells.

14. The system of claim 11 , wherein the physical processor executes machine readable instructions that cause the system to:

access a set of sentiment scores associated with the first attribute, where each sentiment score of the set of the sentiment scores expresses a sentiment associated with the first attribute of a respective data record of the set of data records at a respective time;

aggregate a subset of sentiment scores of the set of sentiment scores within each time interval of a sequence of time intervals;

compute, for a first time interval of the sequence of time intervals, a first aggregate score of a first subset of sentiment scores associated with the first time interval;

wherein the sentiment trend visualization of the particular attribute comprises a graph of the first aggregate score.

15. A non-transitory machine-readable storage medium comprising machine readable instructions that, when executed by a processor, cause a system to:

identify, based on disseminated information from a first geographic region, an event occurring in the first geographic region, wherein the disseminated information from the first geographic region includes public commentary from the first geographic region;

determine a set of attributes related to the event;

extract a set of sentiment words relating to the identified event from the disseminated information, where the extracted set of sentiment words is in a local language of the first geographic region;

associate, for each attribute of the set of attributes, a sentiment from the set of sentiment words; and

cause display of a sentiment trend visualization that depicts a trend of determined sentiments for the first attribute, wherein the determined sentiments are based on the set of sentiment words for the first attribute.

16. The non-transitory machine-readable storage medium of claim 15 , wherein the sentiment trend visualization comprises a set of indicators associated with the identified set of attributes, and wherein the machine readable instructions, when executed, cause the system to:

generate, for the first attribute, an indicator that comprises a set of connected cells, where each cell of the set of connected cells indicates a corresponding sentiment score related to the first attribute.

17. The non-transitory machine-readable storage medium of claim 16 , wherein each cell in the set of connected cells is associated with a corresponding data record in a set of data records determined from the disseminated information, and wherein the set of cells is ordered based on a set of characteristics related to the corresponding set of sentiment scores associated with the set of cells.

18. The non-transitory machine-readable storage medium of claim 15 , wherein the machine readable instructions, when executed, cause the system to:

access a set of sentiment scores associated with the first attribute, where each sentiment score of the set of the sentiment scores expresses a sentiment associated with the first attribute of a respective data record of the set of data records at a respective time;

aggregate a subset of sentiment scores of the set of sentiment scores within each time interval of a sequence of time intervals;

compute, for a first time interval of the sequence of time intervals, a first aggregate score of a first subset of sentiment scores associated with the first time interval;

wherein the sentiment trend visualization of the particular attribute comprises a graph of the first aggregate score.

19. The non-transitory machine-readable storage medium of claim 15 , wherein the machine readable instructions, when executed, cause the system to:

provide for display a list of the identified set of attributes;

receiving selection of a second attribute of the identified set of attributes, where the second attribute is different from the first attribute; and

changing the sentiment trend visualization to depict a second trend of determined sentiments of the second attribute over time.

20. The non-transitory machine-readable storage medium of claim 15 , wherein the identified event comprises a previously unknown event.