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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.

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.

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.

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.

The paper aims to analyse the social responsibility concept and to explore its role in the implementation process of the tourism sustainability concept. The intention is to explore the way in which the social responsibility concept is implemented in the tourism and analyse how it contributes to its sustainability.

In this interpretivist research, the authors implemented a qualitative strategy using the following methods: content, critical and comparative analyses of the results reported in available scientific studies, categorization, causal analysis and mental mapping. The authors identified 14 thematic categories of research on the tourism social responsibility. For the causal description, the authors used driving force, pressure, state, impact, response (DPSIR) method.

The results include identification of the categories of the research topics concerning tourism social responsibility as well as categories of the approaches to the implementation of the social responsibility into the practice of the tourism sector. The causal description of this implementation process is elaborated in the form of the DPSIR model. The created mental map shows the specific facets of the social responsibility concept applied to the diverse tourism subsectors.

The main contribution lies in basic overview of the conceptual (theoretical) and instrumental (practical) base for implementation of the social responsibility concept into the tourism, providing in this way a critical analysis of examples of the social responsibility practice in the key tourism subsectors. The examination of the causal analyses in the form of DPSIR model as well as employment of the content analyses in the form of mental map represent innovative approach to the tourism responsibility research.