ISNA-Set: A novel English Corpus of Iran NEWS

TL;DR

This paper introduces ISNA-Set, a new English news corpus from Iran's ISNA agency, addressing the need for domain-specific datasets to improve natural language processing of online news.

Contribution

The creation and statistical analysis of ISNA-Set, including sentiment, entity extraction, and POS tagging, filling a gap in English news corpora for Iran.

Findings

Statistical analysis of news data

Sentiment analysis results

Entity and POS tagging outcomes

Abstract

News agencies publish news on their websites all over the world. Moreover, creating novel corpuses is necessary to bring natural processing to new domains. Textual processing of online news is challenging in terms of the strategy of collecting data, the complex structure of news websites, and selecting or designing suitable algorithms for processing these types of data. Despite the previous works which focus on creating corpuses for Iran news in Persian, in this paper, we introduce a new corpus for English news of a national news agency. ISNA-Set is a new dataset of English news of Iranian Students News Agency (ISNA), as one of the most famous news agencies in Iran. We statistically analyze the data and the sentiments of news, and also extract entities and part-of-speech tagging.