Promoting science with linguistic devices: A large‐scale study of positive and negative words in academic writing

Abstract

Promotion in science has attracted increasing attention in recent years, and various linguistic devices such as boosters, hypes, or positive words were used to promote research for publication purposes. The present study examined how researchers promote their work with linguistic devices such as positive and negative words and is probably the first one that investigates such promotional devices in not only abstracts but also full texts based on a large dataset of articles (more than 2.2 million). The results showed that the use of positive words in both the abstracts and full texts exhibited a significant uptrend in the past two decades, and positive words were more frequently used than negative ones in both abstracts and full texts. However, journal impact was found to be only very weakly correlated with the use of positive and negative words in both abstracts and full texts. The preference of promotional linguistic devices such as positive words may be explained by factors such as the increasingly competitive selection process of publication, the publication bias, the outcome reporting bias, and the universal positive bias. The study argues for a fair use of such promotional linguistic devices.

Analysis of Rhetorical Appeals to Logos, Ethos and Pathos in ENL and ESL Research Abstracts

“…As supported by this argument, thus the use of emotive words should be able to reflect this domain well (Pennebaker et al, 2015). Furthermore, in relation to the previous literature and the present study, three rhetorical devices identified to reflect emotional tone domain served to evoke the emotional appeal of the writers include the demonstration of rhetorical devices of emotive items in the form of descriptive, negative, and positive words (Pérez-García & Sánchez, 2019;Cao, Lei & Wen, 2020), the passive voice constructions in the expression of ideas (Marquez, 2016;Amnuai, Kotuta & Duangprasertchai, 2020), and sentiment level of the textual writing style (Cao, Lei & Wen, 2020) of the text under consideration.…”

Over‐promotion and caution in abstracts of preprints during the COVID‐19 crisis

“…Many studies have shown that, under normal circumstances, more and more researchers tend to exaggerate the benefit of their research and use a promotional discourse in order to be published, to advance in their career or to obtain funding (Berkenkotter & Huckin, 1995 ; Cao et al, 2020 ; Caulfield & Condit, 2012 ; Vinkers et al, 2015 ). We explore whether the authors are increasingly resorting to positive words and persuasive linguistic devices during the COVID‐19 crisis, in order to be visible or noticeable in the midst of this unprecedented volume of preprints.…”

“…But Berkenkotter and Huckin ( 1995 ) contend that the abstract is essentially a promotional genre where authors underline their most central claims with the aim of gaining readers' attention and persuading them to read on (Sun & Hyland, 2001 ). Cao et al ( 2020 ) showed that positive words are more frequently used in abstracts than in full texts. They consider the abstract as the point at which the reader needs to be ‘hooked’.…”

Conducting Sentiment Analysis

“…This is important because most (i.e., 78 percent) of the movies produced each year are money losers (Davenport & Harris, 2009). Academic writing, being an emerging area for sentiment analysis, has seen a few studies recently (Cao, Lei & Wen, 2020;Vinkers, Tijdink & Otte, 2015;Weidmann, Otto & Kawerau, 2018). The areas of academic writing covered so far are limited to two: biomedical science (Cao et al, 2020;Vinkers et al, 2015) and political science (Weidmann et al, 2018) and the data used have been confined to journal articles and/or their abstracts.…”

“…Academic writing, being an emerging area for sentiment analysis, has seen a few studies recently (Cao, Lei & Wen, 2020;Vinkers, Tijdink & Otte, 2015;Weidmann, Otto & Kawerau, 2018). The areas of academic writing covered so far are limited to two: biomedical science (Cao et al, 2020;Vinkers et al, 2015) and political science (Weidmann et al, 2018) and the data used have been confined to journal articles and/or their abstracts. The methods employed have also been largely simple with a very small sentiment lexicon.…”