Social-topical adaptive networking (STAN) system allowing for cooperative inter-coupling with external social networking systems and other content sources

Abstract

A cross-pollination subsystem is provided within a Social-Topical Adaptive Networking (STAN) system. The cross-pollination subsystem cooperatively interacts with external platforms to bring fresh cross-pollination data to topic nodes or on-topic Notes Exchange rings (TCONE's) of the STAN system. Users are provided with an interface that allows them to browse through the cross-pollinated topic space to thereby connect with online content sources that are likely to correspond to topics of interest currently on the minds of the STAN system users.

Description

1. FIELD OF DISCLOSURE[0001]The present disclosure of invention relates generally to online networking systems and uses thereof. The disclosure relates more specifically to social networking (SN) systems and in particular to cases where one or more social-topical networking (STN) systems are cooperatively coupled to other kinds of online networking and / or content providing systems.2A. CROSS REFERENCE TO CO-OWNED APPLICATION[0002]The following copending U.S. patent application is owned by the owner of the present application, and its disclosure is incorporated herein by reference in its entirety as originally filed:[0003](A) Ser. No. 12 / 369,274 filed Feb. 11, 2009 by Jeffrey A. Rapaport et al. and which is originally entitled, Social Network Driven Indexing System for Instantly Clustering People with Concurrent Focus on Same Topic into On Topic Chat Rooms and / or for Generating On-topic Search Results Tailored to User Preferences Regarding Topic.2B. CROSS REFERENCE TO PATENTS / PUBLICAT...

AI Technical Summary

Benefits of technology

The present patent describes a system that allows two or more social networking systems to cross-pollinate content. This can be done automatically or by a human agent. The cross-pollinated content can include hyperlinks to external platforms, user-to-user interactions, and user-to-topic interactions. The system uses machine-implemented processes to determine the user's current topic of interest and automatically bring relevant content to the user. The content is ranked based on its relevance to the user's topic and the user's position in the topic space. The system also allows users to navigate directly to a content-supplying node and use it as a logical linking source for conveying the latest content to other users. The user's current topic of interest is determined automatically by analyzing the user's actions and facial expressions. Overall, the system improves the user experience by providing relevant content and reducing ambiguity in the user's current topic of interest.

Problems solved by technology

However, even with those two determinations as givens, a term like “bridge” can be highly ambiguous.

However the here disclosed machine system does not operate by magic.

When the mind is forced to jump to an infrastructural level of detail, it can often lose track of the higher-level, substantive material it was concentrating on.

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