{"push_id":2377724696,"size":3,"distinct_size":3,"ref":"refs/heads/master","head":"f3bf8bd3c8a3b6ef027a310ce4c94bd07c862cc3","before":"17143ddf0b07a40b9193f522f6807e2a119c02f7","commits":[{"sha":"9bd69f5cfcffc12211ccd1259cd6aee7d30742e7","author":{"name":"Steboss","email":"afd0682b754a590937c8abd98890071103bd960a@gmail.com"},"message":"Tuned the dictionary, now try to use the comments are a training set","distinct":true,"url":"https://api.github.com/repos/Steboss/lovInstagram/commits/9bd69f5cfcffc12211ccd1259cd6aee7d30742e7"},{"sha":"497b50d4818cf1e99137f7e2ef9f48a38b41d20f","author":{"name":"Steboss","email":"afd0682b754a590937c8abd98890071103bd960a@gmail.com"},"message":"Refined the dictionary of Renzi. Furthermore, I extrapolated 100 positive and 100 negative comments and trained the classifier to recognize better each comment text. The total accuracy of the classifier is 0.85. Overall there are more negative comments than positive one on Renzi's feeds","distinct":true,"url":"https://api.github.com/repos/Steboss/lovInstagram/commits/497b50d4818cf1e99137f7e2ef9f48a38b41d20f"},{"sha":"f3bf8bd3c8a3b6ef027a310ce4c94bd07c862cc3","author":{"name":"Steboss","email":"afd0682b754a590937c8abd98890071103bd960a@gmail.com"},"message":"Refined dictionaries. Now, I extract the positive and negative comments from all the dataset. Manually select 100 pos and 100 neg comments to feed the classifier","distinct":true,"url":"https://api.github.com/repos/Steboss/lovInstagram/commits/f3bf8bd3c8a3b6ef027a310ce4c94bd07c862cc3"}]}
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