A Comparative Study of Keywords and Sentiments of Abstracts by Python Programs

Abstract

Four corpora are created to investigate the self-mentions, keywords and sentiment of abstracts. First, self-mentions are categorized to examine the authorial interactions with the reader. Then, the study of high-frequency words and keywords is conducted with different Python programs and the software AntConc. The keywords generated with WordCloud and TF-IDF-LDA methods show a definite relation with high-frequency words generated by Jieba_Counter and NLTK FreqDist. Further, the sentiment analysis is performed with SnowNLP and TextBlob yielding different results, which verifies the authorial interactions with the reader and increased factual information respectively. Finally, the verification by reference corpora validates the consistency of the sentiment analysis by these two methods. The research suggests that the methods for high-frequency words generation, keywords generation and sentiment analysis be selected discriminatively since different methods generate different results; meanwhile, the study verifies that the objectivity remains in the writing of abstracts. The investigation is conducive to the choices of keywords generation and self-mentions in writing.

The world from the perspective of digital nomads: exploring sentiments in destination reviews

“…It also evaluates the intensity of emotions and can extract noun phrases for analyzing sentiment at a sentence level. It is based on Natural Language Processing (NLP) and the NLTK lexicon (Zhang and Pan, 2020; Bonta et al. , 2019).…”

Exploring Instances of Deleuzian Rhizomatic Patterns in Students’ Writing and in Online Student Interactions

“…A considerable number of studies have been conducted, in which AntConc was used to investigate the lexical bundles and/or phraseology in the written tasks, and to compare the writing patterns of native and non-native speakers of English. Three of these studies are those of Yazıcı and Çıraklı (2019), Ulfa and Muthalib (2020), and Zhang and Pan (2020). These studies have investigated the writing patterns in student writing, even though they did not do so from a rhizomatic perspective.…”