A Study of Stylistic Features of English News Headlines

From different aspects we can draw out different characteristics of news headlines. According to various study and research from different authors, we can conclude their characteristics are displayed on syntactical level, punctuation level, lexical level, rhetorical level and cultural level.

The Stylistic Features of Business English Correspondences and the Cultivation of Business English Competence

Nowadays, with the background of economic globalization, shopping modes like e Bay, Ali Express and Amazon are popular among the public. Business English that plays an increasingly important role in international trades is widely applied to commercial activities. However, because of insufficient practical experience, improper use of stylistics and interference of first language, sometimes it is difficult for students in school to have good command of business English correspondence. This dissertation has suggested learners several ways to improve their competence in international communications and the teaching and learning efficiency, by analyzing the stylistic features of business English correspondences and the problems collecting from the learners on the basis of the data of questionnaires.

Novel Machine Learning–Based Approach for Arabic Text Classification Using Stylistic and Semantic Features

Text classification is an essential task for many applications related to the Natural Language Processing domain.It can be applied in many fields,such as Information Retrieval,Knowledge Extraction,and Knowledge modeling.Even though the importance of this task,Arabic Text Classification tools still suffer from many problems and remain incapable of responding to the increasing volume of Arabic content that circulates on the web or resides in large databases.This paper introduces a novel machine learning-based approach that exclusively uses hybrid(stylistic and semantic)features.First,we clean the Arabic documents and translate them to English using translation tools.Consequently,the semantic features are automatically extracted from the translated documents using an existing database of English topics.Besides,the model automatically extracts from the textual content a set of stylistic features such as word and character frequencies and punctuation.Therefore,we obtain 3 types of features:semantic,stylistic and hybrid.Using each time,a different type of feature,we performed an in-depth comparison study of nine well-known Machine Learning models to evaluate our approach and used a standard Arabic corpus.The obtained results show that Neural Network outperforms other models and provides good performances using hybrid features(F1-score=0.88%).

MEANINGS AND STYLISTIC FEATURES OF“ODE TO THE WEST WIND”

赫罗尔德·布卢姆在《雪莱的神话虚构》一书中说:“‘西风颂’在雪莱抒情诗中独占鳌头,它生动而简洁地概括了抒情体诗的精髓。”本文在剖析西风作用于枯叶、乱云和波浪的过程中指出:西风扮演护持者和破坏者的角色是贯穿全诗的两个主题,而 leaves 是连结全诗的链环。本文作者进而从 seeds 的基督形象、azure 的色彩含义、Maenad 的意象作用、西风的音响效果以及 seeds 与 words 的内在联系等方面作为布卢姆论断精辟的左证。

A Stylistic Analysis of Washington Irving's Stratford-on-Avon

Washington Irving's Stratford-on-Avon is an essay which recounts the author's special pilgrimage to Shakespeare's hometown and his reflections.This paper tries to analyze the essay from the stylistic perspective and reveals the writer's mentality,attitudes and presuppositions through the conveyance of meaning and evaluation of his language.

A Stylistic Appreciation of the Solitary Reaper

The Solitary Reaper is one of the representative works of William Wordsworth.The poem is simple in language but unique in style,so it is very meaningful to appreciate the stylistic style of the Solitary Reaper.Although previous studies have dabbled in this poem,the appreciation of its style is negligible.This paper conducts a more comprehensive stylistic analysis of the poem from such five levels as the graphological level,the phonological level,the lexical level,the syntactic level and the semantic level,thus highlighting the lonely image of the reaper,making readers better understand the style,and showing Wordsworth's love for nature as well as sympathy for the labouring people.

Author’s Age and Gender Prediction on Hotel Review Using Machine Learning Techniques

Author’s Profile(AP)may only be displayed as an article,similar to text collection of material,and must differentiate between gender,age,education,occupation,local language,and relative personality traits.In several informationrelated fields,including security,forensics,and marketing,and medicine,AP prediction is a significant issue.For instance,it is important to comprehend who wrote the harassing communication.In essence,from a marketing perspective,businesses will get to know one another through examining items and websites on the internet.Accordingly,they will direct their efforts towards a certain gender or age restriction based on the kind of individuals who comment on their products.Recently many approaches have been presented many techniques to automatically detect user age and gender from the language which is based on text,documents,or comments on social media.The purpose of this research is to classify age(18–24,25–34,35–49,50–64,and 65–70)and gender(male,female)from a PAN 2014 Hotel Reviews dataset of the English language.The usage of six machine learning models is the main emphasis of this work,including the methods of Support Vector Machine(SVM),Random Forest(RF),Naive Bayes(NB),Logistic Regression(LR),Decision Tree(DT)and K-Nearest Neighbors(KNN).