Bots in journalism: discursive patterns of news created by Artificial Intelligence and news written by humans
Abstract
Sports journalism is increasingly employing artificial intelligence (AI) to automate the generation of notes in events of great coverage. However, it is necessary to recognize that there are discursive differences between the news written by AI and those written by humans. The objective of this work was to identify discursive patterns in the tweets generated by the artificial intelligence called OlyBot and by sports journalists in the Olympic Games of Rio de Janeiro 2016 and Pyeongchang 2018. Gunning's fog index was applied to analyze a sample of 30 tweets issued by the automated system and 30 tweets issued by journalists, in each event. The results indicate that the wording of this AI is simple and concise, as it uses only one sentence per tweet. The parts of speech found were: nouns, verbs, and adjectives. In Rio de Janeiro 2016, both journalists (10.54) and bot (10.44) issued notes that can be read without difficulty, according to the Gunning Fog Index. The most relevant result was found in the readability analysis of the notes issued in Pyeongchang 2018, where journalists reached a value of 14.63 against OlyBot's 10.8, indicating, according to the model used, that these are difficult-to-read texts, which are not for popular consumption. With the increase in words, the artificial intelligence bot maintained its readability level in both events, while the journalist increased the complexity of his notes, making them more unintelligible. The implications of these reflections are of interest to technologists, journalists, and linguists, as well as to society in general since they present the challenge of discerning and assessing those texts that can currently be created by automatons or by journalists, without undermining their readability.
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