The power of prediction with social media

  title={The power of prediction with social media},
  author={Harald Schoen and Daniel Gayo-Avello and Panagiotis Takis Metaxas and Eni Mustafaraj and Markus Strohmaier and Peter A. Gloor},
  journal={Internet Res.},
– Social media provide an impressive amount of data about users and their interactions, thereby offering computer and social scientists, economists, and statisticians – among others – new opportunities for research. Arguably, one of the most interesting lines of work is that of predicting future events and developments from social media data. However, current work is fragmented and lacks of widely accepted evaluation approaches. Moreover, since the first techniques emerged rather recently… 

Social Media and Forecasting:What is the Predictive Power of Social Media

The emergence and growing usage of Social Media has resulted in extremely vast amounts of data that can be collected and accumulated. Businesses are furthermore increasingly interested in using

Social media prediction: a literature review

The research indicates that results are ambiguous, as not all forecasting models can predict with high accuracy, and prediction seems dependable on the associated field, although some of the documented attempts are promising.

Using Social Media to Predict the Future: A Systematic Literature Review

It is found that SM forecasting is limited by data biases, noisy data, lack of generalizable results, a lack of domain-specific theory, and underlying complexity in many prediction tasks, but recurring findings and promising results continue to galvanize researchers and demand continued investigation.

On Predictability of Rare Events Leveraging Social Media: A Machine Learning Perspective

A machine learning framework that leverages social media streams to automatically identify and predict the outcomes of soccer matches in which at least one of the possible outcomes is deemed as highly unlikely by professional bookmakers is developed.

What the Future Holds for Social Media Data Analysis

The current state of research in the area of SM mining and predictive analysis is examined and an overview of the analysis methods using opinion mining and machine learning techniques are given.

The emergence of social media data and sentiment analysis in election prediction

This work presents and assesses the power of various volumetric, sentiment, and social network approaches to predict crucial decisions from online social media platforms and suggests some future directions in respective election prediction using social media content.

Social Media and Forecasting: What is the potential of Social Media as a forecasting tool?

In pursuance of retaining a competitive advantage on the market, businesses continuously ought to be ahead of time, meaning that they have to produce innovative products which respond to customer

Going Back in Time to Predict the Future - The Complex Role of the Data Collection Period in Social Media Analytics

It is found that the choice of time period greatly affected the results obtained, and the model based on pre-event data in 2015 showed considerable accuracy in predicting the 2016 results, illustrating the usefulness of social media data for predicting the outcomes of events outside social media.

Social media analytics system for action inspection on social networks

A real-world case study is reported on, showing how the SocMINT system meaningfully captures trends in public opinion, comparing the main KPIs provided by SocMint with the outcomes of traditional polls.

Analyzing Public Opinion with Social Media Data during Election Periods: A Selective Literature Review

There have been many studies that applied a data-driven analysis method to social media data, and some have even argued that this method can replace traditional polls. However, some other studies



Understanding the predictive power of social media

A proposed conceptual framework for the use of social media data for predictions in various areas, such as disease outbreaks, product sales, stock market volatility and elections outcome predictions, reveals that all relevant studies can be decomposed into a small number of steps.

Predicting the Future with Social Media

  • S. AsurB. Huberman
  • Computer Science
    2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology
  • 2010

Predicting Personality from Twitter

This paper presents a method by which a user's personality can be accurately predicted through the publicly available information on their Twitter profile, and the implications this has for social media design, interface design, and broader domains.

A Meta-Analysis of State-of-the-Art Electoral Prediction From Twitter Data

It is revealed that its presumed predictive power regarding electoral prediction has been somewhat exaggerated and further work on this topic is required, along with tighter integration with traditional electoral forecasting research.

Predicting information credibility in time-sensitive social media

The purpose of the research is to establish if an automatic discovery process of relevant and credible news events can be achieved and to focus on the analysis of information credibility on Twitter.

A user-centric model of voting intention from Social Media

A novel approach which performs high quality filtering automatically, through modelling not just words but also users, framed as a bilinear model with a sparse regulariser is presented.

Nowcasting Events from the Social Web with Statistical Learning

A general methodology for inferring the occurrence and magnitude of an event or phenomenon by exploring the rich amount of unstructured textual information on the social part of the Web by investigating two case studies of geo-tagged user posts on the microblogging service of Twitter.

Predicting Depression via Social Media

It is found that social media contains useful signals for characterizing the onset of depression in individuals, as measured through decrease in social activity, raised negative affect, highly clustered egonetworks, heightened relational and medicinal concerns, and greater expression of religious involvement.

Sentiment Analysis and Opinion Mining

  • Lei ZhangB. Liu
  • Computer Science
    Encyclopedia of Machine Learning and Data Mining
  • 2012
This book is a comprehensive introductory and survey text that covers all important topics and the latest developments in the field with over 400 references and is suitable for students, researchers and practitioners who are interested in social media analysis in general and sentiment analysis in particular.

Social Media and the Elections

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.