Yeroniomus

Thanks a lot for the suggestions and feedbacks to everyone. My nearest plans: small interface redesign, improvement of sentiment analysis algorithm, personalization of news feeds and the iOS launch. Keep on updates!

Yes, not very good screenshot for the landing page. But all of the predictions were made by AI :-)

Not now. It does a general prediction. Maybe I will add this feature in future releases.

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.)

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.

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.

The app uses algorithms of sentiment analysis https://en.wikipedia.org/wiki/Sentiment_analysis All news classify by their positive/negative features. A lot of news sources for different languages were analyzed to automatically extract the typical "good" or "bad" patterns for classification.

Thanks a lot for your recommendations about the UI and the app in general. I'll update it in a near future. It's my first Android project ("just for fun") and I hope you will use SentiNews from time to time.

> Very little content, only like 5 articles from each newspaper. All news are mostly political.

You can swipe beetwen pages and see different news topics (not only politic news). SentiNews includes a lot of categories (Sport, Technology, Science and etc.) from the most popular news sources.

The app uses algorithms of sentiment analysis https://en.wikipedia.org/wiki/Sentiment_analysis All news classify by their positive/negative features. The set of features was created with the help of deep learning technique. A lot of news sources for different languages were analyzed to automatically extract the typical "good" or "bad" patterns for classification.

The main idea was to avoid negative news content with the help of sentiment analysis algorithms. It detects good/bad news articles automatically. So you can read about only good things that happens in the world.

Yes, we are working on the Android version now. Chrome extension will be the next step of this project.

Check this useful article https://www.linkedin.com/pulse/comparison-linguistic-apis-na... about comparison of quality of different text analysis API.

Os X users may use our online version http://esapi.intellexer.com/Summarizer or free mobile version of our another product Conceptmeister https://itunes.apple.com/us/app/conceptmeister-free/id110682... Conceptmeister graps main ideas from text or photo (we use special OCR technology to recognize and extract text from photos)

You may use our online summarizer http://esapi.intellexer.com/Summarizer absolutely for free

Thanks for your feedback. I'll consider this critique for my future submissions. Did you try http://esapi.intellexer.com/Summarizer? It's free online version of the service mentioned in my previous post https://news.ycombinator.com/item?id=12509106.