This data collection provides comprehensive data on all Hindu-Muslim riots reported in the major Indian newspaper of record (THE TIMES of India, Bombay edition), from January 1950 through December 1995. The dataset includes information on location (town, village, state, district, country), casualties, duration, reported causes, official involvement, policing arrangements, and other characteristics.

The religious dataset consisting of Hindu and Muslim hate comments from Bangladesh and India in the Bangla language is a collection of online comments that contain religious hate speech targeting either the Hindu or Muslim communities. These comments were gathered from various sources such as newspapers, social media platforms, and online forums. The purpose of collecting this data is to analyze the prevalence of religious intolerance, identify patterns in hate speech, and contribute to the development of tools for automatically detecting and mitigating such content.

Key Features of the Dataset: Source and Collection:

Comments were sourced from both Bangladesh and India, reflecting religious sentiments in these neighboring countries where tensions between religious groups have often been a social issue. Sources include Bangla-language social media, news articles, opinion pieces, and comments sections on websites.

Content: The dataset contains a mix of both Hindu-targeted hate speech and Muslim-targeted hate speech, with derogatory, offensive, and inflammatory remarks based on religion. Hate comments include stereotypical statements, incitement to violence, communal hatred, and discriminatory language directed at members of the opposing community.

Purpose and Use Cases: Hate Speech Detection: This dataset is useful for developing machine learning models that can automatically identify and flag harmful content on social media platforms. Social Science Research: Researchers can study the psychological and sociopolitical factors that drive such hate speech. Policy and Moderation Tools: Governments, social media platforms, and civil society organizations can use insights from this dataset to design anti-hate speech policies and create moderation systems that reduce online hate.

Challenges: Contextual Nuances: Understanding the cultural and religious context of Bangla comments is crucial for accurately identifying hate speech. A comment that might seem neutral in one context could be deeply offensive in another. Code-Switching: Some comments might mix Bangla with English or regional languages, complicating the classification and sentiment analysis process. Bias in Data: The dataset might reflect a certain level of social bias depending on the region from which it was collected, which needs to be addressed when training AI models.

Conclusion: This dataset offers valuable insights into the dynamics of religious hate speech in Bangladesh and India, two countries with diverse religious populations and a history of interfaith tension. It can help in the development of tools for mitigating online hate speech, while also fostering better understanding and tolerance across religious communities.

record abstracts(1) This is the only version of this data collection to be released through ICPSR. For details about the earlier version contact the principal investigators directly. (2) The current data are being released as an Excel file due to the fact that further processing would truncate valuable information contained in the data. (3) These data are being released as is. Minimal processing was performed. (4) If the user chooses to enhance the file, please submit the enhancements to ICPSR for inclusion in the collection. This data collection provides comprehensive data on all Hindu-Muslim riots reported in the major Indian newspaper of record (THE TIMES of India, Bombay edition), from January 1950 through December 1995. The dataset includes information on location (town, village, state, district, country), casualties, duration, reported causes, official involvement, policing arrangements, and other characteristics. All Hindu-Muslim riots reported in every issue of THE TIMES of India (Bombay) from 1950 through 1995. Datasets: DS1: Varshney-Wilkinson Dataset on Hindu-Muslim Violence in India, 1950-1995, Version 2

India Census: Population: by Religion: Muslim: Urban data was reported at 68,740,419.000 Person in 2011. This records an increase from the previous number of 49,393,496.000 Person for 2001. India Census: Population: by Religion: Muslim: Urban data is updated yearly, averaging 59,066,957.500 Person from Mar 2001 (Median) to 2011, with 2 observations. The data reached an all-time high of 68,740,419.000 Person in 2011 and a record low of 49,393,496.000 Person in 2001. India Census: Population: by Religion: Muslim: Urban data remains active status in CEIC and is reported by Census of India. The data is categorized under India Premium Database’s Demographic – Table IN.GAE001: Census: Population: by Religion.

This study is Pew Research Center's most comprehensive, in-depth exploration of India to date. For this report, Pew surveyed 29,999 Indian adults (including 22,975 who identify as Hindu, 3,336 who identify as Muslim, 1,782 who identify as Sikh, 1,011 who identify as Christian, 719 who identify as Buddhist, 109 who identify as Jain and 67 who identify as belonging to another religion or as religiously unaffiliated). Interviews for this nationally representative survey were conducted face-to-face under the direction of RTI International from November 17, 2019, to March 23, 2020. Respondents were surveyed about religious beliefs and practices, religious identity, nationalism, and tolerance in Indian society.

Understanding the micro-motives for political violence remains an important challenge to contemporary peace research. This paper contributes to this goal in two ways. First and most importantly, it addresses the following research question: what explains hostile sentiments between Hindus and Muslims in cities all across India? To this end, three high- profile theories are reviewed below: elite manipulation, security dilemmas, and prejudice.

This Dataset contains All India, State, Gender of the Head of Household and Religion-wise Total Number of Households

Note: Religion includes Buddhist, Christian, Hindu, Jain, Muslim, Others, Sikh

The dataset contain the primary census abstract categorised by religion in Kerala. The list contains different religions including Hindu, Buddhist, Christian, Muslim, Jain, Sikh etc.. along with the region specifying whether it is urban or rural. The data is of the 2011 census.

The dataset contain the primary census abstract categorised by religion in Delhi. The list contains different religions including Hindu, Buddhist, Christian, Muslim, Jain, Sikh etc.. along with the region specifying whether it is urban or rural. The data is of the 2011 census.

This dataset explores marriage trends in India, comparing love marriages and arranged marriages across various demographic, social, and economic factors. I, capturing key aspects such as age at marriage, caste and religion dynamics, parental approval, dowry exchange, marital satisfaction, divorce rates, income levels, and urban-rural differences.

The dataset aims to provide valuable insights into changing marriage patterns, the role of tradition vs. modernity, and their impact on marital outcomes. Researchers, sociologists, and data analysts can use this dataset to study relationship trends, predict marriage success, and analyze social influences on marriage in India.

ID – Unique identifier

Marriage_Type – Love / Arranged

Age_at_Marriage – Age of the person at marriage

Gender – Male / Female

Education_Level – School / Graduate / Postgraduate / PhD

Caste_Match – Same / Different

Religion – Hindu / Muslim / Christian / Sikh / Others

Parental_Approval – Yes / No / Partial

Urban_Rural – Urban / Rural

Dowry_Exchanged – Yes / No / Not Disclosed

Marital_Satisfaction – Low / Medium / High

Divorce_Status – Yes / No

Children_Count – Number of children (0-5)

Income_Level – Low / Middle / High

Years_Since_Marriage – Number of years since marriage

Spouse_Working – Yes / No

Inter-Caste – Yes / No

Inter-Religion – Yes / No

The dataset contain the primary census abstract divided by religion. The list contains different religions including Hindu, Buddhist, Christian, Muslim, Jain, Sikh etc.. along with the region specifying urban or rura.

The dataset contain the primary census abstract categorised by religion in Assam. The list contains different religions including Hindu, Buddhist, Christian, Muslim, Jain, Sikh etc.. along with the region specifying whether it is urban or rural. The data is of the 2011 census.

The catalog contains data related to Households by Religion, Sex of the Head of the Household and Household Size, Census 2001 - India and States. It includes data on Households, Household Size, Religion like Hindu, Muslim, Christian, Sikh, Buddhist, Jain.

This data set contains experimental data collected as part of the field experiments conducted in West Bengal. These experiments study the effect of religious identity and religious fragmentation on cooperation, rent-seeking and income distribution among Hindu and Muslim groups.

We study the effect of religious identity among Hindu and Muslim groups by varying the way our subjects are matched with each other. We implement in-group/in-group treatments where Muslim subjects play with fellow Muslim subjects and Hindu subjects play with fellow Hindu subjects; we also implement in-group/out-group treatments where Hindu subjects play with Muslim subjects. Finally, we have a control treatment where the identity of a subject's match is uncertain. To study the effect of fragmentation, we resort to a quasi-experimental approach. We take religious composition of villages as fixed, based on the village-level survey on religious fragmentation by Das et al. (2011). We select villages in two districts in West Bengal which conform to one of three categories: Muslim-dominated, where over 90% of the population is Muslim; Hindu-dominated, where over 90% of the population is Hindu; and fragmented, where the Muslim and Hindu communities are roughly equal. Our experimental design combines identity treatments with village types to understand how social identity interacts with fragmentation.

For more details on the analysis of the data, please see the link to the first working paper to have come out of this project, which can be found in the "Related Resources" section.

Tackling increasing resource scarcity is one of the major challenges to policy-makers in developing countries. An important aspect of resource scarcity involves public goods. Lack of public goods, like health and education, can significantly reduce the welfare of individuals and households and often this affects the poorest the most. In India, these issues are amplified by the existence of a long-standing social structure based around caste and religion. Such social fragmentation can result in social exclusion and/or lower public good provision.

This project investigates the behavioural foundations of inter-group discrimination on economic performance in rural West Bengal, India. It builds on existing household survey work on religious- and caste-based social exclusion in villages in West Bengal by conducting a series of field experiments.

Field experiments study the decisions of agents who in their daily lives are affected by poverty, and help determine the extent to which their preferences regarding caste, ethnicity and religion determine their willingness to socially exclude others or themselves to be excluded.

This project‘s findings will help policy-makers to the extent that they facilitate the identification of the right policy response to social exclusion and lower economic performance, which in turn are key determinants of poverty.

A person marital status indicates whether the person is married. It also provides the information on State Code, District Code, Tehsil Code, Area Name, Persons, Males, Females, Religious communities, Hindu, Muslim, Christian, Sikh, Buddhist and Jain etc.

The dataset contain the primary census abstract categorised by religion in Maharashtra. The list contains different religions including Hindu, Buddhist, Christian, Muslim, Jain, Sikh etc.. along with the region specifying whether it is urban or rural. The data is of the 2011 census.

The dataset contain the primary census abstract categorised by religion in Madhya Pradesh. The list contains different religions including Hindu, Buddhist, Christian, Muslim, Jain, Sikh etc.. along with the region specifying whether it is urban or rural. The data is of the 2011 census.

The dataset contain the primary census abstract categorised by religion in Odisha. The list contains different religions including Hindu, Buddhist, Christian, Muslim, Jain, Sikh etc.. along with the region specifying whether it is urban or rural. The data is of the 2011 census.

The dataset contain the primary census abstract categorised by religion in Daman and Diu. The list contains different religions including Hindu, Buddhist, Christian, Muslim, Jain, Sikh etc.. along with the region specifying whether it is urban or rural. The data is of the 2011 census.

The dataset contain the primary census abstract categorised by religion in Himachal Pradesh. The list contains different religions including Hindu, Buddhist, Christian, Muslim, Jain, Sikh etc.. along with the region specifying whether it is urban or rural. The data is of the 2011 census.