CSCI8380 (Spring 2012): Paper Review Form
Reviewer Name: Anuj Shetye
Paper Name: Information creditability on Twitter
Section I. Overview
A. Reader Interest
1. Which category describes this manuscript?
___Practice/Application/Case Study/Experience Report
_X__Research/Technology
___Survey/Tutorial/How-To
B. Content
The authors of this paper focus on automated methods for information creditability of news
propagated on twitter. The authors classify tweets credible or not by specifically analyzing the
micro blog postings related to recent topics based on features extracted from them.
C. Presentation
1.
Does the introduction state the objectives of the manuscript in terms that encourage
the reader to read on?
_X__Yes
___Could be improved
___No
2. How would you rate the organization of the manuscript? Is it focused? Is the length
appropriate for the topic?
_X__Satisfactory
___Could be improved
___Poor
3. Please rate and comment on the readability of this manuscript.
___Easy to read
_X__Readable - but requires some effort to understand
___Difficult to read and understand
___Unreadable
Section II. Evaluation
Please rate the manuscript. Explain your choice.
___Award Quality
___Excellent
_X__Good
___Fair
___Poor
Section III. Detailed Comments (provide your thoughts/criticism about the ideas in the
paper; not only summarize the paper but have a critical look here)
The paper talks about creditability of information on twitter, a popular micro blogging
website. The authors analyze tweets on micro blogs and classify them as credible or not
credible based on some features extracted from them. The researchers focus on the
feature extraction like no. of followers, age and the url to the source website using
Amazon mechanical turks to analyze the information. The methods use J48 decision tree
algorithm which is good but should have been described more. The evaluations are done
by human assessment rather than employing an automated method.
Additional Comments:
1. Provide one aspect that you liked the most in this paper.


The use of J48 decision trees
The authors did extensive evaluations on their proposed method.
2. Provide one aspect that you disliked the most in this paper.

They rely mostly on human assessments rather than trying to automate this
stuff to.
Section IV. Discussion Points (provide at least 3 discussion topics/questions related to
ideas/techniques described in the paper; these will be used for discussions in the class)
1. The J48 decision tree has the tweet with url at the root node, but how do we
decide that the URL itself is credible ?
2. Information credibility will matter most when it is done at real time. The paper
talks about tweets after a certain amount of time has passed.