1. Breaking the News: First Impressions Matter on Online News
Julio Reis, Fabrício Benevenuto, Pedro Vaz de Melo, Raquel Prates
Federal University of Minas Gerais (UFMG), Brazil
Haewoon Kwak and Jisun An
Qatar Computing Research Institute, Qatar

2. Online News Online news industry is very competitive
Many news sites
Lots of news articles are written every day
News sites need to create effective strategies to catch people’s attention
Headlines (the first impressions) are key
Sometimes headlines can be aggressive, exaggerated, and even misleading

3. Goals and Research Questions
Our goal is to provide a measurement study that explains part of what drives the news production and consumption.
Research Questions
How is the sentiment of the news produced by popular newspapers?
Do extremely negative or positive news are able to attract more clicks?
How are users reactions to news articles with different sentiments associated to them?
1) Do they produce more positive, neutral, or negative?
2) In other words, it is worth creating extreme or exagereted headlines?
3) Does the sentiment polarity of users comments reflect the polarity of the news headline?

4. Methodology Gathering News Inferring News Popularity
Measuring News Sentiments

5. Methodology Gathering News Inferring News Popularity
Gathered daily news for 8 months from 4 online news sites
Gathering News
Inferring News Popularity
Measuring News Sentiments
Total of
70K News

6. Methodology We used Bit.ly Gathering News Inferring News Popularity
Gathered statistics 20 days later the news was posted
E.g. bit.ly/1cXzn9o
Gathering News
Inferring News Popularity
Measuring News Sentiments

7. Methodology Gathering News Focus on Headlines
Infer sentiment from sentence-level techniques
Which method to use?
Results vary widely with the data [COSN’13]
We do not know which method is better for this dataset
Gathering News
Inferring News Popularity
Measuring News Sentiments

8. Methodology Gathering News www.ifeel.dcc.ufmg.br [WWW’14]
Implements 20 methods
We labeled 100 headlines to test which method would be suitable
We choose SentiStrength
Among the best for our dataset
Gives sentiment scores from -5 to 5
Gathering News
Inferring News Popularity
Measuring News Sentiments

9. How is the sentiment of online news?
There are much more negative news!

10. How is the sentiment of online news?
Dailymail
The New York Times
Even across categories, there are much more negative than positive news

11. Do positive or negative news attract more clicks?
Neutral headlines tend to be less popular

12. Sentiment of Comments
About 75% of the comments are negative, even across categories and for positive and neutral news

13. Conclusion
This paper investigate patterns of news creation and consumption
Gathered 70 thousands news from NYT, BBC, Reuters, and Dailymail
Inferred: Category, Popularity, Sentiment
Key findings:
Predominance of negative news
Neutral headlines are less popular
Implications for ranking and predictive systems
Comments are negative
Even across categories
Even positive news attract mostly negative comments

14. Datasets are available for research purposes
Thank you!
Datasets are available for research purposes