This is home for my research publications, each linked with accompanying DOI.

Written by Dr. Manika Lamba

Exploring OCR Errors in Full-Text Large Documents: A Study of LIS Theses and Dissertations

Abstract The accuracy of OCR output for text mining and NLP analyses of large text documents can be impacted by errors that occur during the OCR process. The methodology involves retrieving electronic theses and dissertations (ETDs) for LIS discipline from the ProQuest Dissertations and Theses Global database and manually reviewing the full-text ETDs for OCR problems associated with the conversion of PDF files into plain text format.

By 👩‍🔬Manika Lamba, Margam Madhusudhan in Article 2023

How to better engage with ASIS&T members? Lessons learned from SIG-III activities during the COVID-19 pandemic

Abstract Collaborative engagement with members is crucial to sustained membership in professional associations. It also empowers members to connect, grow, and build relationships across large special interest groups (SIGs) within a widely networked organization. Disengagement, social disconnectedness, and lack of belonging among members are challenges that professional associations deal with at an increasing pace. The ASIS&T SIG-International Information Issues (SIG-III) has over 600 members. One of the challenges of having such a large member base is maintaining engagement and finding ways to connect with an international community of academics and information professionals.

By Devendra Potnis, Bhakti Gala, Vanessa Reyes,👩‍🔬 Manika Lamba, Nosheen Fatima Warraich, Leili Seifi, Paul Jason Perez in Panel 2023

D/Misinformation on social media and the role of the LIS profession - A South Asian perspective

Abstract The spread of d/misinformation on social media poses serious threats to the social, cultural, political, and economic structures of human societies. This panel is designed to discuss the phenomenon of d/misinformation and fake news on social media, including the motives of its sharing and its impact on society. The panelists will also highlight the role of LIS professionals in educating society to assess the quality of online information before decision-making.

By Amara Malik, Syeda Hina Batool, Naresh Kumar Agarwal, Prasadi Kanchana Jayasekara, Reshma Dangol,👩‍🔬 Manika Lamba in Panel 2023

Topic Modelling and its Application in Libraries: a review of specialized literature

Abstract Text mining application is one of the most trending and highly researched areas in social sciences. Todate, library professionals’ knowledge of text mining tools and practice is mainly limited, resultantly,the library community poorly understands the full range of issues related to text mining. This articleprovides information on applying a text mining approach called topic modelling in the library andinformation science domain. Topic modelling is a text mining approach that determines a generativemodel for documents.

By 👩‍🔬 Manika Lamba, and Margam Madhusudhan in Article 2023