In this paper, I apply linguistic methods of analysis to non-linguistic data, metaphorically equating one with the other and seeking analogies. The productivity of this approach has been proven within the field of Super Linguistics. I argue that developed by computational linguists word embeddings (made with the algorithm word2vec) can shed light on the features of chess moves. Recently, computational linguistics has made a great progress in natural language processing (NLP). Within this field, tools have been developed for machine analysis of morphology, syntax and semantics. Computational linguistics became a stand-alone research area with its conferences (weblink) and actual fields. The experts have developed general principles of text analysis, optimal methods of word counting.

Working from home increases your risk of making mistakes, a study examining the quality of chess play has found. The standard was significantly worse when players competed online instead of face to face, researchers discovered, suggesting that not being in the office is harmful to productivity. They monitored nearly 215,000 chess moves made by players during in-person and digital tournaments, checking them against what was the best play by using artificial intelligence. Such was the impact on performance when playing remotely, it would have taken Norwegian grandmaster Magnus Carlsen, the world's top-rated player, to the same rating as the current 20th-best player, according to Dainis Zegners from Rotterdam School of Management, one of the study's co-authors. He said the research showed that remote working could hinder people's ability to carry out mentally-intense tasks while alone.