Sentiment Analysis is AI-Hard

In a breezy article on sentiment analysis, Alex Wright quotes Bo Pang saying:

We are dealing with sentiment that can be expressed in subtle ways.

This is so true with the examples I've encountered while working and my favorite is this one I saw on iTunes recently.


While I commend Alex for writing an informative yet accessible article on the topic, I disagree with the article's opinion that sentiment analysis is a series of "filters". That is clearly an euphemism. Any working sentiment analysis system is actually an engineering feat often consisting of a series of hacks duct-taped by a glue handling special cases.

The article also seems to suggest that extracting factual information is somehow easier than opinions. I invite them to participate here.

On the way to Brewer's Art

Never mind how we got to this topic:

me: Parsing is for fogies.

Markus: What?

Jason: I think he means crusty old linguists.

Markus: You should probably use a shallow parser.

me: I'm shallower than that; I use n-grams.

EACL Reading

EACL 2009 accepted paper list is up. Here's my reading list:

WEAKLY SUPERVISED PART-OF-SPEECH TAGGING FOR RESOURCE-SCARCE LANGUAGES
Kazi Saidul Hasan and Vincent Ng

USING CYCLES AND QUASI-CYCLES TO DISAMBIGUATE DICTIONARY GLOSSES
Roberto Navigli

SYNTACTIC AND SEMANTIC KERNELS FOR SHORT TEXT PAIR CATEGORIZATION
Alessandro Moschitti

SENTIMENT SUMMARIZATION: EVALUATING AND LEARNING USER PREFERENCES
Kevin Lerman, Sasha Blair-Goldensohn and Ryan McDonald

PERSON IDENTIFICATION FROM TEXT AND SPEECH GENRE SAMPLES
Jade Goldstein-Stewart, Ransom Winder and Roberta Sabin

OUTCLASSING WIKIPEDIA IN OPEN-DOMAIN INFORMATION EXTRACTION: WEAKLY-SUPERVISED ACQUISITION OF ATTRIBUTES OVER CONCEPTUAL HIERARCHIES
Marius Pasca

GROWING FINELY-DISCRIMINATING TAXONOMIES FROM SEEDS OF VARYING QUALITY AND SIZE
Tony Veale, Guofu Li and Yanfen Hao

GENERATING A NON-ENGLISH SUBJECTIVITY LEXICON: RELATIONS THAT MATTER
Valentin Jijkoun and Katja Hofmann

CONTEXTUAL PHRASE-LEVEL POLARITY ANALYSIS USING LEXICAL AFFECT SCORING AND SYNTACTIC N-GRAMS
Apoorv Agarwal, Fadi Biadsy and Kathleen Mckeown

COMPANY-ORIENTED EXTRACTIVE SUMMARIZATION OF FINANCIAL NEWS
Katja Filippova, Mihai Surdeanu, Massimiliano Ciaramita and Hugo Zaragoza

ANALYSING WIKIPEDIA AND GOLD-STANDARD CORPORA FOR NER TRAINING
Joel Nothman, Tara Murphy and James R. Curran

And we're back ...

Sometime back I wrote about Wordle to visualize textual information using frequency counts. Change.gov, Obama's transition team website uses it on the comments in response to their health care system. This is very interesting but I think Wordle should display top 100 collocations instead of top 100 words. But oh, we also learnt at last ACL how to learn collocation information from unigram frequencies.

Too many cooks?

Computational Linguistics is becoming like the Science or Nature. For instance, see this paper in the current issue: (In this case, the broth wasn't spoiled ;-)

Guess which paper has the largest number of authors on the ACL anthology?

To theory or not to theory

I stumbled upon this paper "Reflections after Refereeing Papers for NIPS" by Leo Breiman that gives some really candid insights into theory papers. (Unfortunately, I could not find a soft copy to share, except this link.) Some noteworthy observations:

"No theorems" implies "No theory"

"... more than 99% of the published papers are useless exercises."

"Mathematical theory is not critical to development of machine learning."

"Our fields would be better off with far fewer theorems, less emphasis on faddish stuff, and much more into scientific inquiry and engineering."

I really liked this article, especially coming from someone who has been working in theory all his life but I would still prefer reading papers giving theoretical insight, however useless, than pages and pages of feature engineering & experimentation using classifier X on problem Y -- the current trend at ACL.

A quick scan at ACL

Mendicant Bug informs about a new tag-cloud service called Wordle. Here is a look at this year's ACL. Gives a clear idea of what is going on! A larger image is available here.