Search results

1 – 6 of 6
Content available

Abstract

Details

Journal of Enterprise Information Management, vol. 30 no. 1
Type: Research Article
ISSN: 1741-0398

Content available

Abstract

Details

On the Horizon, vol. 14 no. 3
Type: Research Article
ISSN: 1074-8121

Keywords

Content available
Article
Publication date: 12 August 2014

Zahir Irani and Muhammad Kamal

417

Abstract

Details

Transforming Government: People, Process and Policy, vol. 8 no. 3
Type: Research Article
ISSN: 1750-6166

Content available
Article
Publication date: 8 February 2016

Zahir Irani and Muhammad Kamal

294

Abstract

Details

Journal of Enterprise Information Management, vol. 29 no. 1
Type: Research Article
ISSN: 1741-0398

Content available

Abstract

Details

Journal of Advances in Management Research, vol. 15 no. 2
Type: Research Article
ISSN: 0972-7981

Open Access
Article
Publication date: 2 June 2021

Shruti Gulati

Twitter is the most widely used platform with an open network; hence, tourists often resort to Twitter to share their travel experiences, satisfaction/dissatisfaction and other…

1465

Abstract

Purpose

Twitter is the most widely used platform with an open network; hence, tourists often resort to Twitter to share their travel experiences, satisfaction/dissatisfaction and other opinions. This study is divided into two sections, first to provide a framework for understanding public sentiments through Twitter for tourism insights, second to provide real-time insights of three Indian heritage sites i.e., the Taj Mahal, Red Fort and Golden Temple by extracting 5,000 tweets each (n = 15,000) using Twitter API. Results are interpreted using NRC emotion lexicon and data visualisation using R.

Design/methodology/approach

This study attempts to understand the public sentiment on three globally acclaimed Indian heritage sites, i.e. the Taj Mahal, Red Fort and Golden temple using a step-by-step approach, hence proposing a framework using Twitter analytics. Extensive use of various packages of R programming from the libraries has been done for various purposes such as extraction, processing and analysing the data from Twitter. A total of 15,000 tweets from January 2015 to January 2021 were collected of the three sites using different key words. An exploratory design and data visualisation technique has been used to interpret results.

Findings

After data processing, 12,409 sentiments are extracted. Amongst the three tourists' spots, the greatest number of positive sentiments is for the Taj Mahal and Golden temple with approximately 25% each. While the most negative sentiment can be seen for the Red Fort (17%). Amongst the positive emotions, the maximum joy sentiment (12%) can be seen in the Golden Temple and trust (21%) in the Red Fort. In terms of negative emotions, fear (13%) can be seen in the Red fort. Overall, India's heritage sites have a positive sentiment (20%), which surpasses the negative sentiment (13%). And can be said that the overall polarity is towards positive.

Originality/value

This study provides a framework on how to use Twitter for tourism insights through text mining public sentiments and provides real- time insights from famous Indian heritage sites.

Details

International Hospitality Review, vol. 36 no. 2
Type: Research Article
ISSN: 2516-8142

Keywords

Access

Only content I have access to

Year

Content type

1 – 6 of 6