Comments (6)
I faced the same challenge. Is there is a work around to it?
I did however found an alternate way of working with vader. It seems NLTK has an inbuilt vader support as well. You can try working with --
from nltk.sentiment.vader import SentimentIntensityAnalyzer
sid = SentimentIntensityAnalyzer()
sid.polarity_scores(text)
The question remains, if the two implementation yield different results or not since they both are using the same lexicon, when I compared the source code.
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having this same problem. Windows 10, Python 3.5
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This happens with Python 3.5 version only. This works well on 2.7. How to fix this error with Python 3.5?
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Having this same error with python 3 anybody if there is a fix now
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I changed the return statement to this:
return dict(map(lambda wm: (wm[0], float(wm[1])), [wmsr.strip().split('\t')[0:2] for wmsr in open(f) ]))
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Thanks! The new update (with new pip install) has better compatibility support for Python 3.
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Related Issues (20)
- Dictionary contains phrases like "fed up" that will never hit because of how the sentence is tokenized HOT 1
- Is NLP still required when using VADER?
- vaderSentiment data output in a different order than specified in the docs
- Wrong weight assigned for hashtags with capitals
- Doubt about threshold values used in VADER categorization
- is this thing still alive?
- incorrect result while running on large dataset HOT 1
- Demo None Type not Iterable HOT 2
- Adding Turkish words HOT 2
- help with adding values to vader_lexicon.txt HOT 1
- Download additional DATASETS AND TESTING RESOURCES mentioned in README HOT 3
- Total dataset is decreasing after processed by VADER
- VADER can't parse the word 'bad ass'? HOT 2
- Positive score always 0? HOT 2
- `SPECIAL_CASES` do not work HOT 2
- Support for new Emojis
- list index out of range error persists... HOT 1
- Supporting Aspect Based sentiment analysis
- Add Julia Fork Link To ReadMe
- the sentimentIntensityAnalyzer VADER is giving results only on emojicon logic and NOT text
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