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Are there any APIs that can extract moods from a string (for use in PHP but can be implemented in any language)?
If one doesn't exist, how would I go about building a classifier, presumably something related to machine learning, where I extract words with known positive/negativity.
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Emotion recognition in a text document is fundamentally a content-based classification issue, including notions from natural language processing (NLP) and deep learning fields. Hence, in this study, deep learning assisted semantic text analysis (DLSTA) has been proposed for human emotion detection using big data.
Go to Analysis > Twitter > Analyze Tweets and select all twitter documents that you would like to include in your analysis. The results will be shown in a table, which includes information about the author and the tweet (for example, how often the tweet has been retweeted or the number of likes a tweet received).
Polarity classification of tweets refers to the task of assigning a positive or a negative sentiment to an entire tweet. Quite similar is predicting the polarity of a specific target phrase, for instance @Microsoft or #Linux, which is contained in the tweet.
Get Sentiments: For e.g.: if a tweet has 4 positive, 2 neutral and, 2 negative words, then the sentiment of the tweet will be calculated as: Thus, the tweet would be marked as positive as it has more positive dominant words.
I would suggest AlchemyAPI. They have pretty simple APIs ( which shouldn't be difficult to use. For your specific case, look into here
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