OPINION MINING WITH ABSTRACTIVE SUMMARIZATION

The pervasive nature of online communication is creating monstrous amounts of data on an un-precedential scale. As a result, the volume of opinioned text is growing. These opinions that are shared online are becoming central to almost all human activities by incredibly impacting the decision-making process. Interesting and actionable political insights could be mined. Working on the premise that online social media conversations might represent a new source of information to monitor the status of the policies launched by the government, this book pioneered and may ultimately be the source for analyzing the data. The platform considered is Twitter as it is all about staying informed and updated which goes well with our problem.

This book provides the reader with the process of extracting the user generated content, formulating a model to classify the tweets and to generate abstractive summaries. This study is vital for opinion mining applications that are beneficial for policy makers, government sectors and social organizations. Later the development of an integrated framework for automated opinion mining system with abstractive summarization is presented.  Additionally, this book introduces “Scheme Critic”, an interface which gathers, analyzes and summarizes the user’s opinions on policies.  Governments around the globe are moving towards building electronic government applications and services. So, the application “Scheme Critic” which was discussed would be embedded into such e-governance systems to aid their decision-making process.

This book includes various applications and discussion of the experiments conducted which can be used as a springboard when readers take up an analysis related to opinion mining. The goal of this book is to provide in depth analysis to the fascinating problem with a research oriented view and experimentation.