Adobe, Inc.

Raman Gupta

Neha Saxena

Ashish Duggal

Piyush Gupta

Niraj Gupta

Anuj Jain

Pulkit Agarwal

A digital medium environment is described to control a start time at which a skippable video advertisement made available by an advertisement provider begins playback at a client. A skippable video advertisement is selected for playback by the client. Data is queried that identifies a skip time corresponding to a time within the skippable video advertisement at which the skippable video advertisement was skipped during a previous viewing of the skippable video advertisement by a user of the client. One of a plurality of start times associated with the skippable video advertisement is then selected based at least in part on the skip time. The skippable video advertisement and the selected start time are then provided to the client effective to cause the skippable video advertisement to begin playback at the selected start time.

Controlling start times at which skippable video advertisements begin playback in a digital medium environment

Audience segmentation can be based on a viewing angle of a user viewing a video of a multi-angle viewing environment. During playback, a sequence of the user-controlled viewing angles of the video are recorded. The sequence represents the viewing angle of the user at a given point in time. Based on the sequences of several users, a predominant sequence of viewing angles of the video is determined. One or more audience segment tags are assigned to the predominant sequence of viewing angles. During subsequent playbacks of the video, the sequence(s) of user-controlled viewing angles of the video are recorded. The recorded sequence(s) of the subsequent user(s) are compared to the predominant sequence of viewing angles of the video, and the subsequent user(s) are assigned to an audience segment based on the comparison and the corresponding audience segment tags.

Audience segmentation based on viewing angle of a user viewing a video of a multi-angle viewing environment

A computer implemented method and apparatus for acquiring sentiment analysis information based on user reactions to displayable content. The method comprises receiving reaction data of at least one individual user viewing portions of displayable content, wherein the reaction data of each user includes indications representative of at least one of a time-varying emotional state of the user and a time-varying level of interest of the user captured during viewing of the displayable content; and performing sentiment analysis on the reaction data by at least one of: categorizing portions of the displayable content based on one of the reaction of one user or aggregated reactions of a plurality of users, and identifying at least one portion of the displayable content having one of a more favorable and a less favorable reaction by the at least one user, by comparison to one of a baseline and reactions to other portions of the displayable content.

Method and apparatus for performing sentiment analysis based on user reactions to displayable content

Video character-based content targeting is described. In one or more embodiments, users make selections of characters in video content in conjunction with playback of the video content. For example, a user is prompted during playback of video content to select a character in the video content that the user likes. An indication is received of selections made by the user of one or more characters, each of which is associated with information that describes a degree to which the character exhibits a plurality of personality attributes. Once received, the user's selections of the one or more characters from the video content are analyzed. In particular, the selections are analyzed to ascertain a degree to which the user identifies with the plurality of personality attributes. The degree to which the user is determined to identify with the plurality of personality attributes is then used to control communication of content to the user.

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Bahadurgarh, India

Raman Gupta