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Empire.Kred - Grow your Social Audience - Empire.Kred

#artificialintelligence

Complete social Missions to discover new content and Influencers that are relevant to you, while your Kred Score grows in real time. Buy and sell on the Social Stock Market, investing your wealth in a booming economy of Influencers. Use your earnings to create Missions which promote content that matters to you. Putting in the time to build a network is challenging, but Empire.Kred has been the encouragement I've needed to persevere - Gord Holden Empire.Kred is all about connecting Influencers with relevant content and rewarding them for it. Complete Social Missions to discover relevant content based on your interests.


15 Steps to Social Media Marketing Success [INFOGRAPHIC]

#artificialintelligence

As social network penetration is ever increasing, it's essential that marketing teams are planning and implementing their social media strategies. As of 2018, there are over 2.6 billion social network users worldwide; in 2010 there were just over 900 million. Social media marketing is a powerful tool, when done correctly, can produce overwhelming results. Ensuring that you have enough time and dedication to apply to your strategy is essential. All it takes is a little planning and guidance to get you on the road to success.


Social Consciousness - Timeline

#artificialintelligence

"Do not, my friends, be led by the deceiver. It is only by pursuing the entire truth, and acting wisely, that humanity can ever survive. So draw the line and sp...eak. Speak out and up, speak the truth and do so compassionately, speak for your children, for those you care about, for the rights of all, and be sure to say clearly: stop!"


Jones

AAAI Conferences

Community discovery in social networks has received a significant amount of attention in the social me- dia research community. The techniques developed by the community have become quite adept at identifying the large communities in a network, but often neglect smaller communities. Evaluation techniques also show this bias, as the resolution limit problem in modular- ity indicates. Small communities, however, account for a higher proportion of a social network's community membership and reveal important information about the members of these communities. In this work, we intro- duce a re-weighting method to improve both the over- all performance of community detection algorithms and performance on small community detection.


Song

AAAI Conferences

With the rapid development of signed social networks in which therelationships between two nodes can be either positive (indicatingrelations such as like) or negative (indicating relations such asdislike), producing a personalized ranking list with positive linkson the top and negative links at the bottom is becoming anincreasingly important task. To accomplish it, we propose ageneralized AUC (GAUC) to quantify the ranking performance ofpotential links (including positive, negative, and unknown statuslinks) in partially observed signed social networks.