Twitter, Inc.

Richard Douglas Whitcomb, Jr

Michael Ben Fleischman

Mark Watabe

Andrew John Carroll

Matthew Miller

Anthony Sciola

Deb Kumar Roy

Jeremy Rishel

Noah Vihinen

Indranrita Deshmukh

Artur B Adib

Wangfan Fu

Thanabordi Jianrungsang

A messaging system automatically populates a stream of messages using only a seed selected by the requesting account holder. In one embodiment, the seed includes the streams of one or more of the 'top' accounts of the messaging system . Here, 'top' is according to any one of a number of different metrics stored in the messaging system. With knowledge of the seed, the messaging system automatically populates a stream for the requesting account holder, without requiring any other input. As a result, an account holder is provided with a fully functioning stream with very little effort or knowledge required on their part.

Automated social message stream population

A messaging system automatically populates a stream of messages using only a seed selected by the requesting account holder. In one embodiment, the seed includes the streams of one or more of the 'top' accounts of the messaging system. Here, 'top' is according to any one of a number of different metrics stored in the messaging system. With knowledge of the seed, the messaging system automatically populates a stream for the requesting account holder, without requiring any other input. As a result, an account holder is provided with a fully functioning stream with very little effort or knowledge required on their part.

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

Images of key phrases or hashtags appear on televised feeds. Image processing techniques, such as feature locating algorithms or character recognition algorithms, can be used to locate the images of key phrases in the images. Then, character recognition algorithms can be used to generate a list of candidate key phrases for the key phrase in image format. However, identification of the key phrase in image format is not completely accurate with conventional methods. Social media content items associated with the televised feed are used to filter the list of candidate key phrases. Using known information about the televised feed as well as about key phrases in text format in the social media content items, candidate key phrases in the list of candidate key phrases can be scored and, thus, a final candidate key phrase selected based on the scores.

Television key phrase detection

Growing community of inventors

Winchester, MA, United States of America

Richard Douglas Whitcomb, Jr