Breaking the News: First Impressions Matter on Online News

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Presentation transcript:

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

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

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?

Methodology Gathering News Inferring News Popularity Measuring News Sentiments

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

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

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

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

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

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

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

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

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

Datasets are available for research purposes Thank you! Datasets are available for research purposes www.dcc.ufmg.br/~fabricio fabricio@dcc.ufmg.br