Twitter

The Comprehensive Hindi Hostile Post Detection Dataset (CM-HTHPD) is collection of Twitter posts written in the Hindi language, focusing on various forms of hostile content. The dataset was gathered using the Twitter Developer API and subsequently annotated manually with sentiment labels using the Label Studio platform. The dataset is primarily aimed at facilitating research and analysis in the domain of hostile content detection and sentiment analysis in Hindi-language social media discourse. The size of the dataset is approx 8300.

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TThe dataset contains Tweet IDs related to Twitter communication in the field of corporate social responsibility, which were downloaded for the period from January 1, 2017 to April 31, 2022. These are 520,638 from 168,134 different users. This dataset contained all tweets containing the hashtag #csr for the period under study.

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TThe dataset contains Tweet IDs related to Twitter communication in the field of corporate social responsibility, which were downloaded for the period from January 1, 2017 to April 31, 2022. These are 520,638 from 168,134 different users. This dataset contained all tweets containing the hashtag #csr for the period under study.

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TThe dataset contains Tweet IDs related to Twitter communication in the field of corporate social responsibility, which were downloaded for the period from January 1, 2017 to April 31, 2022. These are 520,638 from 168,134 different users. This dataset contained all tweets containing the hashtag #csr for the period under study.

Categories:
Views

TThe dataset contains Tweet IDs related to Twitter communication in the field of corporate social responsibility, which were downloaded for the period from January 1, 2017 to April 31, 2022. These are 520,638 from 168,134 different users. This dataset contained all tweets containing the hashtag #csr for the period under study.

Categories:
Views

TThe dataset contains Tweet IDs related to Twitter communication in the field of corporate social responsibility, which were downloaded for the period from January 1, 2017 to April 31, 2022. These are 520,638 from 168,134 different users. This dataset contained all tweets containing the hashtag #csr for the period under study.

Categories:
8 Views

TThe dataset contains Tweet IDs related to Twitter communication in the field of corporate social responsibility, which were downloaded for the period from January 1, 2017 to April 31, 2022. These are 520,638 from 168,134 different users. This dataset contained all tweets containing the hashtag #csr for the period under study.

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<p>This multilingual Twitter dataset spans over 2 years from October 2019 to the end of 2021,&nbsp;including 3 months before the outbreak of the COVID-19&nbsp;pandemic.</p>

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The presence of organisations in Online Social Networks (OSNs) has motivated malicious users to look for attack vectors, which are then used to increase the possibility of carrying out successful attacks and obtaining either private information or access to the organisation. This article hypothesised that organisations have specific languages that their members use in OSNs, which malicious users could potentially use to carry out an impersonation attack.

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