Manika Lamba is a Ph.D. candidate at the Department of Library and Information Science, University of Delhi, India. She is currently serving as the Editor-in-Chief of the International Journal of Library and Information Services (IJLIS), the Elected Standing Committee Member for IFLA Science and Technology Libraries Section, and Newsletter Officer for ASIS&T South Asia Chapter. She was Editor-at-large for dh+lib (an ACRL Digital Humanities Interest Group project) and was featured in the Information Professionals Share their Top Tips for 2019 blog by the Copyright Clearance Center (CCC). She is an active reviewer for more than 17 international journals, including IEEE Access, Scientometrics, Library Hi-Tech, and the Journal of Information Science. Her scholarship focuses on the intersections of computational social science, social informatics, information retrieval, services, and management.

Margam Madhusudhan is currently working as a Professor in the Department of Library and Information Science, University of Delhi, India. He has worked as Deputy Dean Academics and Member of Academic Council at the University of Delhi. He is a member of many academic bodies, editorial board of national and international LIS journals. He is the recipient of the "Award for Excellence" (Highly Commended) in 2019, "Excellence in Research" in 2017, P.V. Verghese Award in 2013. He has 22 years of teaching, administration, and research experience at the university level.

Explains the application of various text mining approaches on data retrieved from heterogeneous resources

Includes 14 case studies showing 8 different text mining and visualization approaches

Complemented by a Web site and a Github account containing code, data and Jupyter Notebooks for the case studies

Includes supplementary material: [...]

1. The Computational Library.- 2. Text Data and Where to Find Them?.- 3. Text Pre-Processing.- 4. Topic Modeling.- 5. Network Text Analysis.- 6. Burst Detection.- 7. Sentiment Analysis.- 8. Predictive Modeling.- 9. Information Visualization.- 10. Tools and Techniques for Text Mining and Visualization.- 11. Text Data and Mining Ethics.