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Nowadays, social medias such as Twitter, Memetracker and Blogs have becomepowerful tools to propagate information. They facilitate quick disseminationsequence of information such as news article, blog posts, user's interests andthoughts through large scale. Providing strong means to analyzing socialnetworks structure and how information diffuse through them is essential. Manyrecent studies emphasize on modeling information diffusion and their patternsto gain some useful knowledge. In this paper, we propose a statistical approachto online detect peak points of news when spread over social networks, to thebest of our knowledge has never investigated before. The proposed model usemartingale approach to predict peak points when news reached the peak of itspopularity. Experimental results on real datasets show good performance of ourapproach to online detect these peak points.

A Martingale Approach to Detect Peak of News in Social Network