Abstract: Feedback attribution includes receiving a feedback item pertaining to an entity. It further includes receiving information pertaining to a plurality of candidate sources of the feedback item. It further includes determining a probabilistic mapping between the feedback item and the plurality of candidate sources. Determining the probabilistic mapping comprises determining, for each candidate source in the plurality of individuals, a likelihood that the feedback is attributed to a given candidate source.

Abstract: Probabilistic employee attribution includes receiving a feedback item pertaining to an organization. It further includes extracting a named entity from text of the feedback item. It further includes determining a list of candidate employees of the organization. It further includes determining, for each candidate employee in the list of candidate employees, a corresponding probability that the candidate employee matches to the named entity extracted from the text of the feedback item. It further includes providing output based at least in part on the probability that the candidate employee matches to the named entity extracted from the text in the feedback item.

Abstract: Macro-Attribution of feedback to solicitation includes determining historical time series information pertaining to collected feedback items. It further includes determining historical time series information pertaining to feedback solicitation. It further includes generating, based at least in part on the historical time series information pertaining to the collected feedback items and the historical time series information pertaining to the feedback solicitation, a macro-attribution model usable to estimate an expected number of feedback items to be received for a time period. It further includes receiving a set of feedback items for the time period. It further includes using the macro-attribution model to determine, for the feedback items received for the time period, an estimate of an amount of feedback that was generated organically, and an estimate of an amount of feedback that was generated by solicitation.

Abstract: Auditing of page profile data on sources is disclosed. Normalized reference location data associated with attributes of an entity location are obtained. Page data from the profile of the entity location on a source is collected. The collected page data is normalized. It is determined whether the page data on the profile of the entity location on the source is valid at least in part by comparing the normalized collected page data against the normalized reference listing data. An audit score is assigned to the profile of the entity location on the source based at least in part on the validity determination. Output is provided based at least in part on the audit.

Abstract: Entity scoring calibration includes receiving values for a metric by which to calibrate a reputation scoring model. The reputation scoring model is usable to determine a reputation score. The reputation scoring model to be calibrated is based at least in part on a set of model parameters associated with reputation scoring components. It further includes receiving a plurality of feedback items pertaining to one or more entities. It further includes calibrating the reputation scoring model at least in part by adjusting at least some of the model parameters associated with the reputation scoring components such that reputation scores generated by the calibrated reputation scoring model track the values for the metric.

Abstract: Enterprise reputation evaluation techniques are disclosed. Reputation data extracted from each of a plurality of data sources is received. The reputation data is associated with a plurality of physical locations of an enterprise entity. An aggregate reputation score is determined for the entity using at least a portion of the received data. The aggregate reputation score is provided as output.

Abstract: Facilitating requests of reviews is disclosed. Contact information associated with a potential reviewer is obtained. A message requesting the potential reviewer to write a review for an entity is transmitted. In response to receiving an indication that the potential reviewer has accepted the request to write the review for the entity, a review site on which the potential reviewer should be directed to write the review for the entity is dynamically determined. A device associated with the potential reviewer is directed to a profile page of the entity on the dynamically determined review site.

Abstract: Dynamic object customization is disclosed. A template associated with content to be published on behalf of one or more entities is obtained. The template includes at least one variable. For each entity in the one or more entities, a data store including information pertaining to the entity is queried based at least in part on the at least one variable included in the template. In response to the query, one or more data values corresponding to the at least one variable are obtained. An object is generated based at least in part on the template. The at least one variable is populated using the obtained one or more data values. The generated object is provided as output to be published on behalf of the entity.

Abstract: Recommending reviewers from which to request reviews is disclosed. A list of potential reviewers is received. A determination is made that at least one potential reviewer included in the list of potential reviewers should be targeted with a request to review an entity. The transmission of a review request to the potential reviewer is facilitated.

Abstract: Impact-based strength and weakness determination includes receiving a plurality of industry-wide feedback items, the industry-wide feedback items pertaining to a plurality of entities associated with an industry. It further includes, based at least in part on an evaluation of the plurality of industry-wide feedback items, generating an industry-wide reputation scoring model usable to determine an expected reputation score for a typical entity in the industry based at least in part on a combination of one or more reputation score components. Generating the industry-wide reputation scoring model comprises determining (1) a baseline reputation score, and (2) an expected impact of a reputation score component on reputation scoring for the typical entity in the industry.

Abstract: Auditing of page profile data on sources is disclosed. Normalized reference location data associated with attributes of an entity location are obtained. Page data from the profile of the entity location on a source is collected. The collected page data is normalized. It is determined whether the page data on the profile of the entity location on the source is valid at least in part by comparing the normalized collected page data against the normalized reference listing data. An audit score is assigned to the profile of the entity location on the source based at least in part on the validity determination. Output is provided based at least in part on the audit.

Abstract: Automatic finding of online profiles of an entity location is disclosed. Reference location data for location attributes of an entity location are obtained. A search for a profile of the entity location on a source is performed using at least some of the obtained reference location data. One or more search results are obtained. A search result includes a Uniform Resource Locator (URL) and corresponding search result location data. The search result is evaluated. Evaluating the search result includes normalizing the search result location data included with the search result and comparing the normalized search result location data against the reference location data. Based at least in part on the evaluation, it is determined whether the search result matches to a profile of the entity location on the source. In the event that the search result matches to a profile of the entity location on the source, the search result is provided as output.

Abstract: Virality cause determination includes receiving a plurality of historical feedback items. It further includes bucketing a first feedback item in the plurality of historical feedback items into a first partition of feedback items, and bucketing a second feedback item in the plurality of historical feedback items into a second partition of feedback items. The second partition of feedback items is a baseline partition of feedback items. It further includes determining a set of candidate patterns present in the first partition of feedback items. It further includes determining whether a candidate pattern in the set of candidate patterns is disproportionately associated with the first partition of feedback items relative to the baseline partition of feedback items.

Abstract: Systems and methods of visualization of electronic social network content are disclosed. A monitor may be designated. The monitor may include criteria specifying desired characteristics of mentions of electronic social network content. Electronic social network content, including mentions, is received from one or more electronic social network platforms. A timeline is presented. The timeline can be representative of a period of time corresponding to when at least a portion of the electronic social network content was provided to electronic social network platforms. A plurality of graphical depictions is presented that match the one or more search criteria of the monitor. Each graphical depiction is presented on the timeline at a position corresponding to a time at which the corresponding mention was provided to a corresponding electronic social network platform. An individual graphical depiction may be sized, colored, and/or shaped to convey additional information about the corresponding mention.

Abstract: Local content publishing is disclosed. A queue is obtained. The queue is associated with a geographical region. A set of entities is determined based at least in part on the geographical region associated with the queue. A piece of content assigned to the queue is obtained. The piece of content is published on behalf of the set of entities determined based at least in part on the geographical region associated with the queue.

Abstract: Impact-based strength and weakness determination includes receiving a plurality of industry-wide feedback items, the industry-wide feedback items pertaining to a plurality of entities associated with an industry. It further includes, based at least in part on an evaluation of the plurality of industry-wide feedback items, generating an industry-wide reputation scoring model usable to determine an expected reputation score for a typical entity in the industry based at least in part on a combination of one or more reputation score components. Generating the industry-wide reputation scoring model comprises determining (1) a baseline reputation score, and (2) an expected impact of a reputation score component on reputation scoring for the typical entity in the industry.

Abstract: Entity scoring calibration includes receiving values for a metric by which to calibrate a reputation scoring model. The reputation scoring model is usable to determine a reputation score. The reputation scoring model to be calibrated is based at least in part on a set of model parameters associated with reputation scoring components. It further includes receiving a plurality of feedback items pertaining to one or more entities. It further includes calibrating the reputation scoring model at least in part by adjusting at least some of the model parameters associated with the reputation scoring components such that reputation scores generated by the calibrated reputation scoring model track the values for the metric.

Abstract: Facilitating requests of reviews is disclosed. Contact information associated with a potential reviewer is obtained. A message requesting the potential reviewer to write a review for an entity is transmitted. In response to receiving an indication that the potential reviewer has accepted the request to write the review for the entity, a review site on which the potential reviewer should be directed to write the review for the entity is dynamically determined. A device associated with the potential reviewer is directed to a profile page of the entity on the dynamically determined review site.

Abstract: Determining themes is disclosed. Reputation data extracted from at least one data source is received. The reputation data includes a plurality of user-authored reviews. The presence of a first keyword is detected in a first review. The presence of a second keyword that is different from but associated with the first keyword is detected in a second review. A sentiment for a theme is determined based on the detected presence of the first and second keywords. A report that indicates the sentiment for the theme is provided as output.

Abstract: Automatic finding of online profiles of an entity location is disclosed. Reference location data for location attributes of an entity location are obtained. A search for a profile of the entity location on a source is performed using at least some of the obtained reference location data. One or more search results are obtained. A search result includes a Uniform Resource Locator (URL) and corresponding search result location data. The search result is evaluated. Evaluating the search result includes normalizing the search result location data included with the search result and comparing the normalized search result location data against the reference location data. Based at least in part on the evaluation, it is determined whether the search result matches to a profile of the entity location on the source. In the event that the search result matches to a profile of the entity location on the source, the search result is provided as output.