As social networks gain widespread popularity, they dominate all other forms of communication, particularly among youth (but of course not only). Perhaps this is because of real-time information and opinion exchange; another reason seems to be a virtual world full of friends whose attention is so easily attracted. The research community found an excellent opportunity to build a new infrastructure at the international level, hence the development of natural (unstructured) language processing (NLP) as a new subfield of language engineering integrated with artificial intelligence and computational linguistics.
This second edition focuses on the most essential research areas: the main stages of language processing; the semantic analysis of social media user utterances; and the application of this analysis to, for instance, medicine, government communication, finances, industry, politics, defense and security, disaster response, media monitoring, and predicting voting intentions. Other popular topics raised by the authors include spam detection, privacy, and democracy in social media and evaluation campaigns such as the American Text Retrieval Conference (TREC) or the European Cross-Language Evaluation Forum (CLEF), which provide benchmark datasets and develop measures of NLP task results.
Regarding language processing, readers can learn about typical technologies like text normalization, tokenization, part-of-speech (PoS) tagging, chunking, parsing the text, named entity recognition (NER), and translation tools. Semantic analysis is also a hot topic in research, as it includes geolocalization of the social media participants, sentiment analysis, event or topic detection, and automatic summarization or commonly used machine translation (MT).
The authors organized a workshop where they posed some very interesting questions to participants, which in fact motivated them to study social media. Examples of those questions include: What do people talk about on social media? How do they express themselves? How can the participants be described based on their tweets?
I thoroughly recommend this thought-provoking book to students, researchers, and industry workers.
More reviews about this item: Amazon