Bottlenose, Inc.

Blazent, Inc.

Dominiek Ter Heide

Nova T Spivack

Seyed Ali Mousavi

Systems and methods for presenting a graphical visualization of user related content in a network or across networks are disclosed. In one aspect, embodiments of the present disclosure include analyzing the content from within the network or across the networks, identifying trending topics, and customizing the graphical visualization based on a given topic. The given topic can be user specified and/or can be based on implicit and/or explicit user interests or preferences. The given topic can also be administrator specified. The graphical visualization can present the topics as being connected to the given topic, where the given topic is presented as a center node and the topics relating to that given topic are arranged radially from the center node. The trending topics can change based on a configurable timeframe (e.g., minutes, days, weeks, etc.).

System and method for analyzing messages in a network or across networks

Systems and methods for analyzing messages in a network or across networks are disclosed. In one aspect, embodiments of the present disclosure include a method, for detecting trends from a set of messages in a network or across networks, identifying, from the set of messages in the network or across networks, commonly or frequently occurring topics, computing statistical attributes for the commonly or frequently occurring topics in the set of messages that indicate respective levels of trendiness, and/or presenting, the commonly or frequently occurring topics as indicators in a user interface, the indicators being actionable to access additional information relating to a selected topic via the action. The messages include messages interacted with by humans or machines and interactions can include, posted a message, shared a message, liked a message, commented on a message, replied to a message, viewed a message, saved or bookmarked a message.

A system and a method for microcontent natural language processing are presented. The method comprising steps of receiving a microcontent message from a social networking server, tokenizing the microcontent message into one or more text tokens, performing a topic extraction on the microcontent message to extract topic metadata, generating sentiment metadata for the microcontent message, analyzing co-occurrence of all available metadatas in the plurality of microcontent messages, producing a list that ranks the plurality of microcontent messages based on all available topic metadata, and compiling a trend database that reveals how perception of users of the social networking server on a given topic changes by tracking how the list changes over time.

Machine-based content analysis and user perception tracking of microcontent messages

A system and a method for discovering and ranking trending links about topics are presented. The method comprises steps of receiving a plurality of messages from a social networking server, identifying a plurality of trending objects from the plurality of messages, generating at least one trending score for each trending object of the trending objects, and presenting a list of the trending objects based on the trending scores.

Discovering and ranking trending links about topics

A system and a method for microcontent natural language processing are presented. The method comprising steps of receiving a microcontent message from a social networking server, tokenizing the microcontent message into one or more text tokens, detecting the language of the microcontent message and selecting the property dictionary for part-of-speech tag, part-of-speech tagging the microcontent message to identify related pronouns and nouns based on the selected dictionary, and extracting topics form the microcontent messages and assigning confidence values to the topics.

Natural language processing optimized for micro content

The disclosed techniques can provide users with a tool having an integrated, user-friendly interface and having automated mechanisms which can reveal correlations between data streams to the users in a clear and easily understandable way, thereby enabling the users to easily digest the vast amount of information contained in activities within one or more network, to understand the correlations among the activities, to stay informed and responsive to current or new trends, and even to predict future trends. Among other benefits, the disclosed techniques are especially useful in the context of discovering impacts of social networking activities on other types of commercial activities.

Growing community of inventors

Amsterdam, Netherlands

Dominiek Ter Heide