Dynamics of Hornbill Festival of Nagaland: Exploring Identity Assertion and Cultural Negotiation.
Published In: Journal of the Indian Anthropological Society, 2025, v. 60, n. 3. P. 314 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: PATTON, NOYINGBENI M. 3 of 3
Abstract
The Hornbill Festival, showcasing the customs and heritage of over 17 Naga tribes, is the largest cultural event in the State of Nagaland. This event, which takes place every year in December for ten days, generates an enormous spike in both domestic and foreign culture-conscious visitors to the State. When discussing the Nagas, one of the most commonly mentioned aspects of their history is that their ancestors practiced headhunting. This practice earned them the title of the "headhunters' tribe," and it continues to hold cultural significance, often reflected in their traditional performances. Each year, the festival organizers select a cultural troupe from each tribe to represent as custodians of the unique Naga heritage. The performances encompass various artistic expressions, including folk songs, traditional dances, imitation games depicting hunting or warfare, and more. This research will delve into the intricacies of a variety of performances showcased during the festival, elucidating their cultural significance and meanings held by the people. Furthermore, it explores to what extent the festival can unite diverse Naga communities and evoke a spirit of sharing a common identity among them. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of the Indian Anthropological Society. 2025/11, Vol. 60, Issue 3, p314
- Document Type:Article
- Subject Area:Social Sciences and Humanities
- Publication Date:2025
- ISSN:0019-4387
- Accession Number:189772385
- Copyright Statement:Copyright of Journal of the Indian Anthropological Society is the property of Journal of the Indian Anthropological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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