Bluefin Labs, Inc.

Twitter, Inc.

Hb Innovations, Inc.

Massachusetts Institute of Technology

Happiest Baby, Inc.

Deb Kumar Roy

Michael Ben Fleischman

Jeremy Rishel

Matthew Miller

Anjali Midha

Richard Douglas Whitcomb, Jr

Noah Vihinen

Mark Watabe

Andrew John Carroll

Indranrita Deshmukh

Artur B Adib

Harvey Neil Karp

Jesse V Gray

Matthew R Berlin

Bill Walter Washabaugh

Brandon Cain Roy

Deb Roy - Professor of Media Arts and Sciences

Social media content items are mapped to relevant time-based media events. These mappings are used as the basis for calculating metrics based upon the mappings, and ratings of the time-based media there from. Audience response metrics (ARMs) are calculated from the mappings, which provide an indication of audience engagement or response. In addition, ARMs provide information about the virality, depth, and breadth of the response by the viewing audience. The calculated metrics are stored and are used to generate ratings for the time-based media. The ratings may be published in whole or in part, e.g., as part of a ratings system.

Generating audience response metrics and ratings from social interest in time-based media

An affinity server estimates an affinity between two different time based media events (e.g., TV, radio, social media content stream), between a time based media event and a specific topic, or between two different topics, where the affinity score represents an intersection between the populations of social media users who have authored social media content items regarding the two different events and/or topics. The affinity score represents an estimation of the real world affinity between the real world population of people who have an interest in both time based media events, both topics, or in a time based media event and a topic. One possible threshold for including a social media user in a population may be based on a confidence score that indicates the confidence that one or more social media content items authored by the social media user are relevant to the topic or event in question.

Topic and time based media affinity estimation

A real time messaging platform identifies an audio snippet of a time-based media (TBM) event. The messaging platform maintains a real time repository of concurrently broadcasting TBM events as well as a historical repository of previously broadcast TBM events. These repositories contain acoustic fingerprints of their respective TBM events. The messaging platform matches an acoustic fingerprint of the audio snippet with one of the stored acoustic fingerprints to identify the TBM event in the recorded snippet. To identify the TBM event, the messaging platform matches multiple overlapping reference audio segments of the reference audio stream with multiple test audio segments of the audio snippet. This allows the platform to account for time delays between the test and reference audio segments that would otherwise hinder the matching process.

Identification of concurrently broadcast time-based media

An infant calming/sleep-aid/SIDS detection device is provided that includes a main moving platform that moves in a variable manner with accompanying variable sound generation, the sound and motion adapted to calm a fussy baby, induce sleep, and maintain sleep under normal conditions. The device may also have a sensor for detection of pauses in breathing and/or detection of resultant biological changes related to breathing pauses and respond with appropriate stimuli to arouse the baby and allow breathing to recommence.

Infant calming/sleep-aid, SIDS prevention device, and method of use

Social media content items are mapped to relevant time-based media events. These mappings may be used as the basis for multiple applications, such as ranking of search results for time-based media, automatic recommendations for time-based media, prediction of audience interest for media purchasing/planning, and estimating social interest in the time-based media. Social interest in time-based media (e.g., video and audio streams and recordings) segments is estimated through a process of data ingestion and integration. The estimation process determines social interest in specific events represented as segments in time-based media, such as particular plays in a sporting event, scenes in a television show, or advertisements in an advertising block. The resulting estimates of social interest also can be graphically displayed.

Estimating social interest in time-based media

An infant calming/sleep-aid device includes a main moving platform that moves in a reciprocating manner and an actuator that drives the reciprocating movement of the main moving platform. The moving head platform is linked to the main moving platform and at least one of a motion sensing device and a sound sensing device are either at or proximate to a moving head platform that is pivotally linked to the main moving platform. A logic circuit links at least one of the motion and sound sensing devices of the infant calming/sleep aid-device to the main moving platform whereby signals detected modulate movement of the main moving platform. A sound generating device is linked to the logic circuit.

Growing community of inventors

Arlington, MA, United States of America

Deb Kumar Roy