Historical Tweets

Beard and McNayr introduce thousands of years of tweets, from Adam's first tweet through the beginnings of the modern world to major events of the recent past, in this smart and creative take on the twitter phenomenon. Full color throughout.

The lesson plans in this book enable educators to easily incorporate networking technologies into the classroom—not just a fun enrichment activity, but one that is selective and intentional to teach the required standards. Our Web 2.0 world is based on participation. Incorporating networking sites into classroom lesson plans invites students to participate and get involved using the digital learning styles with which they are already accustomed—interacting with new information, building knowledge, and sharing that knowledge with an authentic, responsive audience. The Networked Library: A Guide for the Educational Use of Social Networking Sites demonstrates how integrating networking tools that students enjoy using can improve their learning in the classroom. The book is designed to take educators who are new to networking sites from the ground up, while allowing experts to jump directly into the lesson plan chapters. It covers many types of networking sites that educators can use to their advantage: media sharing sites, including YouTube, TeacherTube, Wikimedia Commons, and Flickr; microblogs and wikis such as Wikispaces, PBworks, and Twitter; and social networking sites including Facebook, Ning, and Edmodo.

The edited volume Sequences in Language and Text is the first collection of original research in the area of the quantitative analysis of sequentially organized linguistic data. Linguistic sequences are extremely useful textual structures in almost all areas of Language Technology. Character and word n-grams are by far the most successful features in text classification tasks such as authorship identification, text categorization, genre classification, sentiment analysis etc. Furthermore character linguistic sequences are the basis for linguistic modeling and subsequent applications such as speech recognition, language identification etc. In addition to the above language technology oriented research, the present volume aims to give insight to the theoretical value of linguistic sequences. Sequences in texts can be produced by a number of different factors, either external to the linguistic system or by its own grammatical structure. This volume hosts contributions which will analyze linguistic sequences using quantitative methods under the synergetic theoretical framework that can explain their role in the linguistic system.

In the era of technology and big data, advanced and innovative research methods and conducting effective research to solve emerging problems in tourism and hospitality is critical, making Advanced Research Methods in Hospitality and Tourism a necessity for academics and practitioners.

This volume set constitutes the refereed proceedings of the 16th International Conference on Knowledge Science, Engineering and Management, KSEM 2023, which was held in Guangzhou, China, during August 16–18, 2023. The 114 full papers and 30 short papers included in this book were carefully reviewed and selected from 395 submissions. They were organized in topical sections as follows: knowledge science with learning and AI; knowledge engineering research and applications; knowledge management systems; and emerging technologies for knowledge science, engineering and management.

This book proposes new technologies and discusses future solutions for ICT design infrastructures, as reflected in high-quality papers presented at the 4th International Conference on ICT for Sustainable Development (ICT4SD 2019), held in Goa, India, on 5–6 July 2019. The conference provided a valuable forum for cutting-edge research discussions among pioneering researchers, scientists, industrial engineers, and students from all around the world. Bringing together experts from different countries, the book explores a range of central issues from an international perspective.

This book covers deep-learning-based approaches for sentiment analysis, a relatively new, but fast-growing research area, which has significantly changed in the past few years. The book presents a collection of state-of-the-art approaches, focusing on the best-performing, cutting-edge solutions for the most common and difficult challenges faced in sentiment analysis research. Providing detailed explanations of the methodologies, the book is a valuable resource for researchers as well as newcomers to the field.