cjhutto/vaderSentiment

Weightage given to smileys (when negated)

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#28 opened on Apr 4, 2017

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help wanted

Description

So, Vader gives 1.0 positive for " :) " and 1.0 negative for " :( " and with that I know that the smileys are being detected correctly. However, it fails to identify the polarity correctly for this particular case:

sentence = "nothing for redheads :(" polarity got: {'neg': 0.0, 'neu': 0.555, 'pos': 0.445, 'compound': 0.3412}

It is surprising that this sentence is tipping towards the positive polarity while the negative remains at 0.0. Now if I remove the smiley and find the polarity, this is what I get:

sentence = "nothing for redheads" polarity got: {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0}

And this result is absolutely correct. It is a neutral statement. So, why is that a negative lexicon, tending the sentence towards a positive outcome? I wanted to know if I can manipulate the weight of smileys to reduce such errors. Since Vader is capable of handling many tricky sentences, this should not have been an issue right ? or is it just an outlier condition ?

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Tech stack
python
Domain
machine learning
Issue type
bug
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-3 hours
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
clear
Prerequisites
PythonBasic sentiment analysis concepts
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
40
Research direction
Investigate the sentiment boosting logic for smileys in VADER. The issue likely resides in the vaderSentiment library's lexicon handling of emoticons with negation. Check the code in vaderSentiment/sentiment.py, specifically the part that applies modifiers to smiley scores. The user reports that a negative smiley with neutral text yields positive overall; this suggests the negation is not being applied to the smiley's score. Consider if a similar issue exists for positive smileys with negation.