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Show HN: Positive News Reader based on sentiment analysis

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Re: Show HN: Positive News Reader based on sentiment analysis

#3
Hello, Hacker News users! It's my first Android app and first experience of Android development :-). SentiNews is based on sentiment analysis which helps to classify news as positive or negative. What do you think about general concept of the app? Will be waiting for your feedback.

Re: Show HN: Positive News Reader based on sentiment analysis

#6
post #4

Curious to know which algorithm and the sourcing of corpus you chose to train your system on. On a similar note, here a curation of great sentiment analysis methods and implementations: https://github.com/xiamx/awesome-sentiment-analysis

Thanks a lot for the link. I've used the technology called Paragraph Vectors https://cs.stanford.edu/~quocle/paragraph_vector.pdf for sentiment features extraction. Training collections were created in a semi-automatic mode and included news title+short description gathered from popular RSS feeds.

Re: Show HN: Positive News Reader based on sentiment analysis

#7
post #4

Curious to know which algorithm and the sourcing of corpus you chose to train your system on. On a similar note, here a curation of great sentiment analysis methods and implementations: https://github.com/xiamx/awesome-sentiment-analysis

Thanks a lot for the link. I've used the technology called Paragraph Vectors https://cs.stanford.edu/~quocle/paragraph_vector.pdf for sentiment features extraction. Training collections were created in a semi-automatic mode and included news title+short description gathered from popular RSS feeds.

Sentence vectors encode the data, but how do you determine if a story is positive or negative?

Re: Show HN: Positive News Reader based on sentiment analysis

#8

Earlier quoted context omitted.

Thanks a lot for the link. I've used the technology called Paragraph Vectors https://cs.stanford.edu/~quocle/paragraph_vector.pdf for sentiment features extraction. Training collections were created in a semi-automatic mode and included news title+short description gathered from popular RSS feeds.

Sentence vectors encode the data, but how do you determine if a story is positive or negative?

After collection of possible positive/negative features with weights I used logistic regression classifier with some modifications (e.g. position algorithm) to classify the article. It determines the article polarity based on features (words, phrases and etc.)
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