iMeetzu Social Network Allows Users to Publish and Ranks Conversation
Katie Cordrey — November 3, 2009 — Life-Stages
iMeetzu Social Network crowdsources feedback to rate people on their conversational abilities. The iMeetzu website allows users to publish conversations which can then be rated by conversation readers. iMeetzu also facilitates social networking so that favorite chat partners can be contacted after they are no longer strangers.
iMeetzu Social Network founders, two 22-year-old college students, Aaron Mannenbach (Cornell) and Josh Marthaller (University of Oregon) describe the iMeetzu concept as an, “open source conversationalism social network.” The pair has just upgraded the site from its initial bare-bones chat form that launched in July into, “an all new never seen before type of social network.”
iMeetzu Social Network founders, two 22-year-old college students, Aaron Mannenbach (Cornell) and Josh Marthaller (University of Oregon) describe the iMeetzu concept as an, “open source conversationalism social network.” The pair has just upgraded the site from its initial bare-bones chat form that launched in July into, “an all new never seen before type of social network.”
Trend Themes
1. Publicized Conversations - Sites enabling conversation publication for public feedback provide opportunities for new forms of communication analytics.
2. Crowdsourced Ratings - Crowdsourcing chatter evaluations offer insights into the drivers of engaging conversations.
3. Open-source Social Networks - Open-source conversationalism social networks represent a new trend in hybrid social media platforms.
Industry Implications
1. Social Media - The social media industry can leverage conversational data insights to improve user engagement.
2. Analytics - The analytics industry can take advantage of conversational data and trend analysis to provide business insights.
3. Social Networking - Social networking industry players may explore hybrid models that combine traditional social networking functionality with messaging and feedback features.
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