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edit approved May 10, 2017 at 8:05
VividD
edit approved May 10, 2017 at 8:05
VividD
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I wanted to perform Twitter sentiment analysis on Twitter tweets. When I googled it, I found a stanfordNLPstanfordNLP code of sentiment class. I used it for finding Twitter sentiment later I came to know twitter GateTwitterGate model is made for Twitter tweets only.

Then I replaced the stanfordNLPstanfordNLP model with TwitterGateTwitterGate model. I did not find any difference in the sentiment results. Both models give the same result. But

However, when I tested the same tweets with monkeylearn apiMonkeylearn API and datumbox apiDatumbox API sentiment results., I got confused with results. In NLP and twitterGate most tweets sentiment is given as negative, where the same Tweetstweets sentiment is given as neutral in MonkeylearnMonkeylearn & Datumbox apisDatumbox APIs code.

How can I know model which model is giving the correct sentiment?

I wanted to perform Twitter sentiment analysis on Twitter tweets. When I googled it, I found a stanfordNLP code of sentiment class. I used it for finding Twitter sentiment later I came to know twitter Gate model is made for Twitter tweets only.

Then I replaced the stanfordNLP model with TwitterGate model. I did not find any difference in the sentiment results. Both models give the same result. But when I tested same tweets with monkeylearn api and datumbox api sentiment results. I got confused. In NLP and twitterGate most tweets sentiment is given as negative where same Tweets sentiment is given as neutral in Monkeylearn & Datumbox apis code.

How can I know model which is giving the correct sentiment?

I wanted to perform Twitter sentiment analysis on Twitter tweets. When I googled it, I found a stanfordNLP code of sentiment class. I used it for finding Twitter sentiment later I came to know TwitterGate model is made for Twitter tweets only.

Then I replaced the stanfordNLP model with TwitterGate model. I did not find any difference in the sentiment results. Both models give the same result.

However, when I tested the same tweets with Monkeylearn API and Datumbox API sentiment, I got confused with results. In NLP and twitterGate most tweets sentiment is given as negative, where the same tweets sentiment is given as neutral in Monkeylearn & Datumbox APIs code.

How can I know which model is giving the correct sentiment?

Removed " at start of title, and tidied question into paragraphs.
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Neil Slater
Neil Slater
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"How How do I assess which sentiment classifier is best for my project?

I wanted to perform Twitter sentiment analysis on Twitter tweets. So whenWhen I googled it, I found a stanfordNLP code of sentiment class. I used it for finding Twitter sentiment later I came to know twitter Gate model is made for Twitter tweets only. So,

Then I replaced the stanfordNLP model with TwitterGate model. I did not find any difference in the sentiment results.Both Both models give the same result but. But when I tested same tweets with monkeylearn api and datumbox api sentiment results. I got confused. In NLP and twitterGate most tweets sentiment is given as negative where same Tweets sentiment is given as neutral in Monkeylearn & Datumbox apis code. Now 

How can I know model which is giving the correct sentiment?

"How do I assess which sentiment classifier is best for my project?

I wanted to perform Twitter sentiment analysis on Twitter tweets. So when I googled it, I found a stanfordNLP code of sentiment class. I used it for finding Twitter sentiment later I came to know twitter Gate model is made for Twitter tweets only. So, I replaced the stanfordNLP model with TwitterGate model. I did not find any difference in the sentiment results.Both models give the same result but when I tested same tweets with monkeylearn api and datumbox api sentiment results. I got confused. In NLP and twitterGate most tweets sentiment is given as negative where same Tweets sentiment is given as neutral in Monkeylearn & Datumbox apis code. Now How can I know which is giving the correct sentiment?

How do I assess which sentiment classifier is best for my project?

I wanted to perform Twitter sentiment analysis on Twitter tweets. When I googled it, I found a stanfordNLP code of sentiment class. I used it for finding Twitter sentiment later I came to know twitter Gate model is made for Twitter tweets only.

Then I replaced the stanfordNLP model with TwitterGate model. I did not find any difference in the sentiment results. Both models give the same result. But when I tested same tweets with monkeylearn api and datumbox api sentiment results. I got confused. In NLP and twitterGate most tweets sentiment is given as negative where same Tweets sentiment is given as neutral in Monkeylearn & Datumbox apis code. 

How can I know model which is giving the correct sentiment?

edited title
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Dilip Bobby
Dilip Bobby
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How to choose a MachineLearning framework "How do I assess which sentiment classifier is best for my project?

I wanted to perform Twitter sentiment analysis on Twitter tweets. So when I googled it, I found a stanfordNLP code of sentiment class. I used it for finding Twitter sentiment later I came to know twitter Gate model is made for Twitter tweets only. So, I replaced the stanfordNLP model with TwitterGate model. I did not find any difference in the sentiment results.Both models give the same result but when I tested same tweets with monkeylearn api and datumbox api sentiment results. I got confused. In NLP and twitterGate most tweets sentiment is given as negative where same Tweets sentiment is given as neutral in MonkeylearnMonkeylearn & Datumbox apisDatumbox apis code. Now How can I know which is giving the correct sentiment?

How to choose a MachineLearning framework?

I wanted to perform Twitter sentiment analysis on Twitter tweets. So when I googled it, I found a stanfordNLP code of sentiment class. I used it for finding Twitter sentiment later I came to know twitter Gate model is made for Twitter tweets only. So, I replaced the stanfordNLP model with TwitterGate model. I did not find any difference in the sentiment results.Both models give the same result but when I tested same tweets with monkeylearn api and datumbox api sentiment results. I got confused. In NLP and twitterGate most tweets sentiment is given as negative where same Tweets sentiment is given as neutral in Monkeylearn & Datumbox apis code. Now How can I know which is giving the correct sentiment?

"How do I assess which sentiment classifier is best for my project?

I wanted to perform Twitter sentiment analysis on Twitter tweets. So when I googled it, I found a stanfordNLP code of sentiment class. I used it for finding Twitter sentiment later I came to know twitter Gate model is made for Twitter tweets only. So, I replaced the stanfordNLP model with TwitterGate model. I did not find any difference in the sentiment results.Both models give the same result but when I tested same tweets with monkeylearn api and datumbox api sentiment results. I got confused. In NLP and twitterGate most tweets sentiment is given as negative where same Tweets sentiment is given as neutral in Monkeylearn & Datumbox apis code. Now How can I know which is giving the correct sentiment?

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Dilip Bobby
Dilip Bobby
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