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  • Influence
How (Not) to Predict Elections
TLDR
It is found that electoral predictions using the published research methods on Twitter data are not better than chance and a set of standards that any theory aiming to predict elections (or other social events) using social media should follow is proposed. Expand
Limits of Electoral Predictions Using Twitter
TLDR
This work applies techniques that had reportedly led to positive election predictions in the past, on the Twitter data collected from the 2010 US congressional elections, but finds no correlation between the analysis results and the electoral outcomes, contradicting previous reports. Expand
The power of prediction with social media
TLDR
It is argued that statistical models seem to be the most fruitful approach to apply to make predictions from social media data in the field of social media-based prediction and forecasting. Expand
Vocal Minority Versus Silent Majority: Discovering the Opionions of the Long Tail
TLDR
This paper presents results of data analysis that compares two groups of different users: the vocal minority ( users who tweet very often) and the silent majority (users who tweeted only once), and discovers that the content generated by these two groups is significantly different. Expand
Can Collective Sentiment Expressed on Twitter Predict Political Elections?
TLDR
This paper applies methods used in studies that have shown a direct correlation between volume/sentiment of Twitter chatter and future electoral results in a new dataset about political elections to show they are inadequate for determining whether social media messages can predict the outcome of elections. Expand
From Obscurity to Prominence in Minutes: Political Speech and Real-Time Search
Recently, all major search engines introduced a new feature: real-time search results, embedded in the first page of organic search results. The content appearing in these results is pulled byExpand
On the predictability of the U.S. elections through search volume activity
In recent years several researchers have reported that the volume of Google Trends and Twitter chat over time can be used to predict several kinds of social and consumer metrics. From the success ofExpand
Social Media and the Elections
TLDR
Monitoring what users share or search for in social media and on the Web has led to greater insights into what people care about or pay attention to at any moment in time, helping segments of the world population to be informed, to organize, and to react rapidly. Expand
The Visible and Invisible in a MOOC Discussion Forum
TLDR
This analysis of a large MOOC online forum shows that for every active participant in the forum there are two passive ones and that ``invisible activity'' is something that both groups practice equally and more frequently, while only 3.3% of forum actions are visible. Expand
The Fake News Spreading Plague: Was it Preventable?
TLDR
This paper outlines the recipe of how social networks are used to spread misinformation and indicates how it was successfully used tospread fake news during the 2016 U.S. Presidential Election. Expand
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