Comparative Study : Sentiment Analysis using Automated pattern based appraoch VS Single structured model

Papers Compared

1. Enhanced sentiment learning using Twitter hashtags and smileys
2. Structured Models for Fine-to-Coarse Sentiment Analysis

Comparison

Both the paper solve same problem "sentiment classification". But the differences are more then similarities.

Additional Questions

1. How much time did you spend reading the (new, non-wikified) paper you summarized?
   • 2.5 hours
2. How much time did you spend reading the old wikified paper?
   • 1 hour
3. How much time did you spend reading the summary of the old paper?
   • 15 minutes
4. How much time did you spend reading background materiel?
   • None
5. Was there a study plan for the old paper?
   • Yes
   1. if so, did you read any of the items suggested by the study plan? and how much time did you spend with reading them?
      • Yes, I glanced over 2/3 papers to understand the key concepts. It was a good starting point.
      • 45 minutes
6. Give us any additional feedback you might have about this assignment.
   1. The wikified paper's summary was quite useful to start with as it helped in understanding the big picture immediately and noting down the key areas to look for in the paper.
      • For example the binary classification was not immediately clear from summary, evaluation with human judges was a new thing i encountered when i read the paper. I had additional doubt on overlapping hashtags and labels that was explained in paper.
   2. Some additional key features that I had to look for in paper: KNN distance function, Neighbor selection criteria, Feature selection process.
   3. I think its useful to have a good summary and its unavoidable to ignore too much details in summary. But In the current wikified summary some important features were missing and a good discussion on pros and cons of the approach were missing.