DOI: 10.21227/57hq-gm60
title: "Indian BSE Earnings Call Transcripts Dataset: 15,812 Quarterly Corporate Disclosure Documents from 1,362 Listed Firms"

description: "Indian BSE Earnings Call Transcripts Dataset (2011-2025 Q2): 15,812 Quarterly Corporate Disclosure Documents from 1,362 Listed FirmsThis dataset comprises 15,812 verbatim quarterly earnings call transcripts from 1,362 companies listed on the Bombay Stock Exchange (BSE), spanning January 2011 through July 2025 (Quarter 2). Collectively representing approximately 123.9 million words of unstructured financial text, these transcripts capture management discussions, Q&A sessions, and forward-looking statements delivered during quarterly earnings announcements.Dataset Composition:Temporal Coverage: 14.5 years (2011 Q1 - 2025 Q2), with primary focus on 15,812 post-2014 transcripts ensuring BSE reporting standardizationFirm Coverage: 1,362 unique BSE-listed firms across 20+ industry sectorsDocument Statistics: Mean transcript length of 7,835 words (range: 1 - 103,508 words)Industry Distribution: Information Technology, Financial Services, Consumer Goods, Healthcare, Telecommunication, Construction, Energy, and othersFile Format: Plain text (.txt) files organized by company identifier foldersKey Features:Verbatim transcripts including management prepared remarks and analyst Q&A segmentsMulti-sectoral representation covering India's economic landscape from liberalization through digital transformationCaptures critical economic periods: pre-liberalization (2011-2014), liberalization phase (2015-2019), COVID-19 pandemic (2020), economic recovery (2021-2022), and post-pandemic growth (2023-2025)Enables longitudinal analysis of corporate communication strategies, sentiment evolution, and disclosure practicesRaw, unprocessed text suitable for natural language processing (NLP), sentiment analysis, readability assessment, topic modeling, and machine learning applicationsPotential Applications:Financial sentiment analysis and market prediction researchCorporate governance and disclosure quality studiesTextual analytics for emerging market researchNatural language processing benchmarking (dictionary-based vs. transformer models)Information asymmetry and investor communication researchRegulatory compliance analysis (SEBI disclosure mandates)Comparative studies of developed vs. emerging market corporate communicationsEngineering management research on innovation signaling and stakeholder alignmentData Quality:All transcripts have been validated for completeness and formatted consistently. The dataset excludes 1,200 pre-2015 records to ensure BSE reporting maturity and standardization compliance. Files are UTF-8 encoded plain text with minimal preprocessing to preserve original disclosure content.Related Publication:This dataset supports the research published in IEEE Transactions on Engineering Management: \"Advancing Corporate Disclosure Analytics: A Comparative Study of Dictionary-Based and Transformer-Based Models in Indian Earnings Call Transcripts\" (submitted October 2025).License: Creative Commons Attribution 4.0 (CC-BY-4.0)Citation: When using this dataset, please cite both the dataset and the associated research paper."