Extract From the same link (text only as shown below) Highly Positive 0.81!
>The usual German term for the extermination of the Jews during the Nazi period was the euphemistic phrase Endlösung der Judenfrage (the "Final Solution of the Jewish Question"). In both English and German, "Final Solution" is widely used as an alternative to "Holocaust".[16] For a time after World War II, German historians also used the term Völkermord ("genocide"), or in full, der Völkermord an den Juden ("the genocide of the Jewish people"), while the prevalent term in Germany today is either Holocaust or increasingly Shoah.
NLP is H A R D, I know and defining a range value for sentiment even harder.
Re:Ask HN: Review ContextSense - deduces context and sentime...
by paraschopra on Thursday September 10, 2009 @11:44AM
(#815459)
Hey guys, my startup (Wingify) has exposed an API for determining sentiment and context from any URL or piece of text. I'll be glad if you could review it.
ContextSense was made to demonstrate our contextual targeting capabilities -- and sentiment aspect was added to avoid traditional blunders of displaying ads on pages/news on catastrophies. Best to try ContextSense with text heavy URLs. Also try it with news items (both positive and negative).
I will be happy to provide API access in case any of you is interested in trying it out.
Re:Ask HN: Review ContextSense - deduces context and sentime...
by elcron on Thursday September 10, 2009 @05:23PM
(#816230)
Cool! I tried something like this, it classified blog posts into 100 different moods... it had ~8% accuracy (It also classified as positive or negative, but I don't remember the accuracy, I'll have to dig it up at some point...). Good luck with it.
Re:Ask HN: Review ContextSense - deduces context and sentime...
by elcron on Friday September 11, 2009 @02:56PM
(#817871)
It was accurate around 56% of the time classifying as positive, negative, or neutral. I used a naive Bayesian classifier and guessed the highest rather than showing the percent positive.
Few human practices have provoked such deep and widespread outrage as the practice of one human being enslaving another. So why has slavery survived for thousands of years? How did it become so important to civilization? Explore the ways that slavery has been woven into the fabric of societies in America and around the world.
Sentiment: Highly Positive (0.77)
Seems off in cases where the tone of the text is neutral but the subject matter is negative.
Re:Ask HN: Review ContextSense - deduces context and sentime...
by rwolf on Thursday September 10, 2009 @01:55PM
(#815773)
The comments so far refer to the "sentiment deducer" aspect of the service. They've brought up some examples of how it's not working right now, but they missed an important question: what in the world is "positive sentiment" abstracted from context, and why would I want to know if a site had it?
An issue we haven't brought up is tags. Current tags for HN: "ago, points, comments, com, hours, hour, hacker, discuss, minutes, tornado." I see some good ones, but it's quite noisy (and it seems to have grabbed the tornado story as a main topic--scraping the title?). This feature seems most useful to me, and most easy to improve.
Re:Ask HN: Review ContextSense - deduces context and sentime...
by paraschopra on Friday September 11, 2009 @12:15AM
(#816834)
No, not just a title but the whole website. The algo currently works on TF-IDF of the tags, and HN is full of points, ago, hours, etc. repeated all over it. This increases the TF. We would be putting an upper limit on it though.
Re:Ask HN: Review ContextSense - deduces context and sentime...
by rwolf on Friday September 11, 2009 @12:59AM
(#816885)
I didn't mean the title tag--I meant the first story title (the SEO kids talk about google fixating on the first h1 tag of a site, I though it might be a similar idea). I have no idea what this upper limit change would do, but good luck.
The results are better than I would've guessed, but not really so great (this article is pretty degenerate I think, versus more "human-interest" type stories).
One thing I'm curious out: the list of topics is here:
People (7.88)
Algebra (4.47)
Research Groups (3.41)
Software (2.42)
Math (2.03)
Functional Analysis (1.53)
Journals (1.01)
Science (0.71)
Publications (0.64)
Logic and Foundations (0.6)
...does looking at the content give you any sense for why "People" comes in first?
Re:Ask HN: Review ContextSense - deduces context and sentime...
by erikwiffin on Thursday September 10, 2009 @06:19PM
(#816334)
Reading the other comments, it looks like your biggest problems are false positives. It might not be a bad idea to put together some kind of feedback mechanism - in the event that I disagree with the sentiment/tags/categories that I could provide better ones and you could eventually use that data to refine your algorithm.
That being said, this looks really cool and full of potential, now I just need a reason to be auto-generating that kind of meta data.
Re:Ask HN: Review ContextSense - deduces context and sentime...
by onewland on Thursday September 10, 2009 @02:44PM
(#815880)
I think positive/negative is too shallow. I actually do enjoy this, but I think you need to rate sentiments on other vectors, so if I rate http://teddziuba.com/ I get something like:
Anger: 25
Smugness: 50
Vulgarity: 15
Boredom: 5
etc.
I'm not even sure that's a good example or if it's clear, I just think positive/negative is an oversimplification of the sentiment of most sites.
Slightly Negative (0.33)
Extract From the same link (text only as shown below) Highly Positive 0.81!
>The usual German term for the extermination of the Jews during the Nazi period was the euphemistic phrase Endlösung der Judenfrage (the "Final Solution of the Jewish Question"). In both English and German, "Final Solution" is widely used as an alternative to "Holocaust".[16] For a time after World War II, German historians also used the term Völkermord ("genocide"), or in full, der Völkermord an den Juden ("the genocide of the Jewish people"), while the prevalent term in Germany today is either Holocaust or increasingly Shoah.
NLP is H A R D, I know and defining a range value for sentiment even harder.
ContextSense was made to demonstrate our contextual targeting capabilities -- and sentiment aspect was added to avoid traditional blunders of displaying ads on pages/news on catastrophies. Best to try ContextSense with text heavy URLs. Also try it with news items (both positive and negative).
I will be happy to provide API access in case any of you is interested in trying it out.
Few human practices have provoked such deep and widespread outrage as the practice of one human being enslaving another. So why has slavery survived for thousands of years? How did it become so important to civilization? Explore the ways that slavery has been woven into the fabric of societies in America and around the world.
Sentiment: Highly Positive (0.77)
Seems off in cases where the tone of the text is neutral but the subject matter is negative.
An issue we haven't brought up is tags. Current tags for HN: "ago, points, comments, com, hours, hour, hacker, discuss, minutes, tornado." I see some good ones, but it's quite noisy (and it seems to have grabbed the tornado story as a main topic--scraping the title?). This feature seems most useful to me, and most easy to improve.
http://en.wikipedia.org/wiki/C*-algebra
The results are better than I would've guessed, but not really so great (this article is pretty degenerate I think, versus more "human-interest" type stories).
One thing I'm curious out: the list of topics is here:
People (7.88) Algebra (4.47) Research Groups (3.41) Software (2.42) Math (2.03) Functional Analysis (1.53) Journals (1.01) Science (0.71) Publications (0.64) Logic and Foundations (0.6)
...does looking at the content give you any sense for why "People" comes in first?
That being said, this looks really cool and full of potential, now I just need a reason to be auto-generating that kind of meta data.
Anger: 25 Smugness: 50 Vulgarity: 15 Boredom: 5
etc.
I'm not even sure that's a good example or if it's clear, I just think positive/negative is an oversimplification of the sentiment of most sites.
I typically have cookies disable, but I turned them on and it made no difference.