The abundance of text available in social media and health-related forums and blogs have recently attracted the interest of the public health community to use these sources for opinion mining. This book presents a lexicon-based approach to sentiment analysis in the bio-medical domain, i.e., WordNet for Medical Events (WME). This book gives an insight in handling unstructured textual data and converting it to structured machine-processable data in the bio-medical domain.The readers will discover the following key novelties:1) development of a bio-medical lexicon: WME expansion and WME enrichment with additional features.;2) ensemble of machine learning and computational creativity;3) development of microtext analysis techniques to overcome the inconsistency in social communication.It will be of interest to researchers in the fields of socially-intelligent human-machine interaction and biomedical text mining

The abundance of text available in social media and health-related forums and blogs have recently attracted the interest of the public health community to use these sources for opinion mining. This book presents a lexicon-based approach to sentiment analysis in the bio-medical domain, i.e., WordNet for Medical Events (WME). This book gives an insight in handling unstructured textual data and converting it to structured machine-processable data in the bio-medical domain.

The readers will discover the following key novelties:

1) development of a bio-medical lexicon: WME expansion and WME enrichment with additional features.;

2) ensemble of machine learning and computational creativity;

3) development of microtext analysis techniques to overcome the inconsistency in social communication.

It will be of interest to researchers in the fields of socially-intelligent human-machine interaction and biomedical text mining

The abundance of text available in social media and health-related forums and blogs have recently attracted the interest of the public health community to use these sources for opinion mining. This book presents a lexicon-based approach to sentiment analysis in the bio-medical domain, i.e., WordNet for Medical Events (WME). This book gives an insight in handling unstructured textual data and converting it to structured machine-processable data in the bio-medical domain.The readers will discover the following key novelties:1) development of a bio-medical lexicon: WME expansion and WME enrichment with additional features.;2) ensemble of machine learning and computational creativity;3) development of microtext analysis techniques to overcome the inconsistency in social communication.It will be of interest to researchers in the fields of socially-intelligent human-machine interaction and biomedical text mining

The abundance of text available in social media and health-related forums and blogs have recently attracted the interest of the public health community to use these sources for opinion mining. This book presents a lexicon-based approach to sentiment analysis in the bio-medical domain, i.e., WordNet for Medical Events (WME). This book gives an insight in handling unstructured textual data and converting it to structured machine-processable data in the bio-medical domain.

The readers will discover the following key novelties:

1) development of a bio-medical lexicon: WME expansion and WME enrichment with additional features.;

2) ensemble of machine learning and computational creativity;

3) development of microtext analysis techniques to overcome the inconsistency in social communication.

It will be of interest to researchers in the fields of socially-intelligent human-machine interaction and biomedical text mining