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I am trying to understand what the VADER does for analysis of sentences. Why is the hyper-parameter Alpha set to 15 here? I understand that the it is unstable when left unbound, but why 15?

def normalize(score, alpha=15):
"""
Normalize the score to be between -1 and 1 using an alpha that
approximates the max expected value
"""
norm_score = score/math.sqrt((score*score) + alpha)
return norm_score
Photops
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1 Answers1

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Vader's normalization equation is which is the equation for

I have read the paper of the research for Vader from here:http://comp.social.gatech.edu/papers/icwsm14.vader.hutto.pdf

Unfortunately, I could not find any reason why such a formula and 15 as the value for alpha was chosen but the experiments and the graph show that as x grows which is the sum of sentiments' scores grow the value becomes closer to -1 or 1 which indicates that as number of words grow the score tends more towards -1 or 1. Which means that Vader works better with short documents or tweets compared to long documents.

Nareg
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