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Purpose: This chapter explores the two major schemes applicable to skill development in India: Skill Acquisition and Knowledge Awareness for Livelihood Promotion (SANKALP) and Pradhan Mantri Kaushal Vikas Yojana (PMKVY).

Need for the Study: The primary objective of this research is to check the role of these schemes in enhancing the skills of socio-economically stressed community members for their livelihoods. The secondary aim is to analyse the outcomes of these schemes through a qualitative inquiry.

Methodology: A survey was conducted, and the data was collected from trainees of the skill development programmes. Based on the responses, a qualitative content analysis was performed, which showed that most trainees have the thirst and urge to enhance their life skills for a minimalistic livelihood.

Findings: The study concluded that though there are many schemes, only PMKVY is active. They focus on more than just youth communities. Instead, they consider individuals in different age categories.

Practical Implications: The Government of India (GOI) is progressing towards a healthy economy to compete with other countries. For this mission to be achieved, skill and labour development is paramount. Appropriate training must be provided and administrated through government schemes.

Sentiment analysis is a text analysis method that is developed for systematically detecting, identifying, or extracting the emotional intent of words to infer if the text expresses a positive or negative tone. Although this novel method has opened an exciting new avenue for organizational research – mainly due to the abundantly available text data in organizations and the well-developed sentiment analysis techniques, it has also posed a serious challenge to many organizational researchers. This chapter aims to introduce the sentiment analysis method in the text mining area to the organizational research community. In this chapter, the authors first briefly discuss the central role of sentiment in organizational research and then introduce the traditional and modern approaches to sentiment analysis. The authors further delineate research paradigms for text analysis research, advocating the iterative research paradigm (cf., inductive and deductive research paradigms) that is more suitable for text mining research, and also introduce the analytical procedures for sentiment analysis with three stages – discovery, measurement, and inference. More importantly, the authors highlight both the dictionary-based and machine learning (ML) approaches in the measurement stage, with special coverage on deep learning and word embedding techniques as the latest breakthroughs in sentiment and text analyses. Lastly, the authors provide two illustrative examples to demonstrate the applications of sentiment analysis in organizational research. It is the authors’ hope that this chapter – by providing these practical guidelines – will help facilitate more applications of this novel method in organizational research in the future.