I have similarity distribution graph, the graph has cosine similarity distribution values on y axis and relevant dates on x axis.(Datas are coming from a csv file) According to this values i need to find plateu to measure is there any high tension or not (something like is there any bump or not) my graph is as follows ;
The output of graphs is like myoutoutput1. I just calculated max value of graph and min value and average and i drawed a line for each ,also if number of values above the average greater than the number of values below the average then i said it to be a it is a high tension (i mean eventy topic)
what kind of math function should be used to measure that yes there is an event in your graph or not ? may be taking integral or etc.
One of sample for my csv file is like ;
date,close,topic 11-Jul-16,0.3919340235688502,T0 13-Jul-16,0.34676875219073117,T1 17-Jul-16,0.7318672747426419,T1 19-Jul-16,0.551091886884678,T1 21-Jul-16,0.4790156920874872,T4 23-Jul-16,0.49307051752070574,T0 25-Jul-16,0.28283343212895085,T0 27-Jul-16,0.31970262826528034,T0 29-Jul-16,0.4017937576119373,T4 31-Jul-16,0.28103157876820484,T3
for example when value goes from 0.3 to 0.7 there is a valuable increase and it is a tension but 0.3 to 0.5 not an eventy increase.
I mean that if distribution value goes like 5,7,8,10,12,9,8,10 there is no any eventy topic but if it goes like 5,7,8,18,19,9,8,7,5 it is an eventy one.
Actually the following article did what i want but i have trouble with understanding of eventy analysis, (Article:Using Topic Modeling and Similarity Thresholds to Detect Events)
Thanks for your interest and sincerity..