This work presents and assesses the power of various volumetric, sentiment, and social
network approaches to predict crucial decisions from online social media platforms. The …

To what extent does our online activity reveal who we are? Recent research has
demonstrated that the digital traces left by individuals as they browse and interact with …

Medical sciences have long since established an ethics code for experiments, to minimize
the risk of harm to subjects. Natural language processing (NLP) used to involve mostly …

Automatic political orientation prediction from social media posts has to date proven
successful only in distinguishing between publicly declared liberals and conservatives in the …

Income forecasting is always the idea of knowing how many people us are around. Here we
saw how to use machine learning technology to test people's income according to their …

We provide an NLP framework to uncover four linguistic dimensions of political polarization
in social media: topic choice, framing, affect and illocutionary force. We quantify these …

With the development of social networks, a large variety of approaches have been
developed to define users' personalities based on their social activities and language use …

In recent years, online social networking has revolutionized interpersonal communication.
The newer research on language analysis in social media has been increasingly focusing …

As political attitudes have diverged ideologically in the United States, political speech has
diverged lingusitically. The ever-widening polarization between the US political parties is …

Automatically inferring user demographics from social media posts is useful for both social
science research and a range of downstream applications in marketing and politics. We …