Google Inc.

Anders Torp Brodersen

Theodore Kent Hamilton

Keekim Heng

Dror Shimshowitz

Martin Landers

Mirjam Wattenhofer

Jonas Yngvesson

Salvatore Scellato

Tom Broxton

Jakub Petrykowski

Anja Hauth

Andrew Stack

A method includes logging first user interactions associated with a playlist of content items and generating first metrics based on the logged first user interactions with the playlist. The first metrics include a first metric indicating a first duration of playback of a first content item of the playlist during playback of the playlist. The first duration of playback of the first content item during the playback of the playlist is greater than a first default duration of playback. The method further includes reporting at least the first metric to a creator or curator of the playlist, logging second user interactions associated with the playlist, and generating second metrics based on the logged second user interactions with the playlist. The logged first user interactions correspond to more deviations from a default playback sequence of the playlist than the logged second user interactions.

Playlist analytics

A method includes generating metrics based on a first plurality of interactions with first content of a playlist. A first metric indicates approval of a first content item of the playlist and a second metric indicates a first duration of playback of a second content item of the playlist during playback of the playlist. The first duration of playback of the second content item is greater than a first default duration of playback. The method further includes reporting at least the first metric and the second metric and receiving a modified playlist. The modified playlist may be the playlist modified based on at least the first metric. The method further includes identifying, in captured data associated with access to the modified playlist, a second plurality of interactions with second content of the modified playlist. The second plurality of interactions corresponds to fewer deviations than the first plurality of interactions.

Systems and methods are disclosed for providing playlist analytics. A method includes logging first user interactions associated with a playlist of content items and generating metrics based on the logged first user interactions with the playlist. The playlist is associated with a default playback sequence of the content items. A first metric indicates a last content item played by a user from the playlist is different from a last content item in the default playback sequence associated with of the playlist. The method further includes reporting at least the first metric. The playlist is to be modified based on one or more of the plurality of metrics.

Systems and methods can facilitate gathering information generated by network traffic to playlists. Based on analytics and metrics derived from the gathered information and reported, feedback about playlist access patterns can be supplied to interested parties, such as playlist creators/curators. The feedback can enable playlist curators to better tailor playlist content and sequence, potentially reducing a perceived need to skip around inside a playlist and making for a more enjoyable experience for playlist users.

Systems and methods are disclosed for providing playlist analytics. A method may include capturing data associated with access to a playlist of content. The method may further include identifying, in the captured data, one or more interactions with the playlist of content. The method may further include generating, by a processing device, at least one metric based on the identified one or more user interactions. The method may further include reporting the at least one playlist metric.

A mechanism to evaluate the geographic popularity of geographically-located user-generated content is presented. A method to evaluate the geographic popularity of geographically-located user-generated content includes receiving a user-generated content item having metadata indicating a geographic location of the user-generated content item, determining geographic location metadata of each of a plurality of views of the content item, calculating a view geographic entropy of the content item by dividing the plurality of views across multiple geographic regions while taking into account the geographic location of the content item, and providing the calculated view geographic entropy of the content item for presentation in a visual display that is part of an analytical report of the content item.

Mechanism to evaluate the geographic popularity of geographically-located user-generated content items

This disclosure relates to systems and methods for determining source information for subscribe and unsubscribe events to channels, indicating referring sources from which subscribers initiated the events, and presenting the source information to content providers of the channels.

Implicit determination of referral sources for subscriptions to channels

The present invention enables methods and systems that identify viral videos. A viral video is a video which received a percentage of its views from one person sharing the video with another person. That is, a viral video received most of its views from person to person sharing. A video hosting server determines whether a video is a viral video based at least in part on views the video received through person to person sharing and the total number of views the video has received.

Identifying viral videos

Method to evaluate the geographic popularity of geographically located user-generated content items

Methods and systems that identify classic videos. A classic video is a video that consistently receives high viewership over a long period of time. A video hosting server identifies a number of views that a video received for each day during a measurement period. For each day, the video hosting server determines whether the day is a high view day based on the number of views for the day. The video hosting server identifies the video as a classic video responsive to the video having a number of high view days that are above a threshold number of days.

Identifying classic videos

Systems and methods for media access analytics are disclosed herein. When media content such as a video is accessed, typically by a referring link, the referrer can be identified. The referrer can be classified as an internal referrer, an external referrer, a viral referrer, or into another of a set of predefined classes. Statistics associated with access to the media content can be generated according to an associated class of referrer and presented to a user associated with the media content (e.g., a user who uploaded the video) or another authorized party.

Growing community of inventors

Wadenswil, Switzerland

Anders Torp Brodersen