Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities

Artificial intelligence (AI) has captured substantial interest from a wide array of marketing scholars in recent years. Our research contributes to this emerging domain by examining AI technologies in marketing via a global lens. Specifically, our lens focuses on three levels of analysis: country, company, and consumer. Our country-level analysis emphasizes the heterogeneity in economic inequality across countries due to the considerable economic resources necessary for AI adoption. Our company-level analysis focuses on glocalization because while the hardware that underlies these technologies may be global in nature, their application necessitates adaptation to local cultures. Our consumer-level analysis examines consumer ethics and privacy concerns, as AI technologies often collect, store and process a cornucopia of personal data across our globe. Through the prism of these three lenses, we focus on two important dimensions of AI technologies in marketing: (1) human–machine interaction and (2) automated analysis of text, audio, images, and video. We then explore the interaction between these two key dimensions of AI across our three-part global lens to develop a set of research questions for future marketing scholarship in this increasingly important domain.     

Fifty years of The Financial Review: A bibliometric overview

The Financial Review (FR) is a highly regarded journal publishing original empirical, theoretical, and methodological research in all areas of financial economics. It celebrated its golden jubilee year in 2018. Using bibliometric techniques, we analyze the journal's impact, prominent topics, most prolific authors, and their affiliated institutions and countries. Our analysis also identifies the most often cited articles at different points in the journal's history. Using textual data analytics, we identify the most frequent themes discussed between 1969 and 2018 by decade.     

基于改进Transformer模型的文本摘要生成方法

传统的文本摘要方法，如基于循环神经网络和Encoder-Decoder框架构建的摘要生成模型等，在生成文本摘要时存在并行能力不足或长期依赖的性能缺陷，以及文本摘要生成的准确率和流畅度的问题。对此，提出了一种动态词嵌入摘要生成方法。该方法基于改进的Transformer模型，在文本预处理阶段引入先验知识，将ELMo(Embeddings from Language Models)动态词向量作为训练文本的词表征，结合此词对应当句的文本句向量拼接生成输入文本矩阵，将文本矩阵输入到Encoder生成固定长度的文本向量表达，然后通过Decoder将此向量表达解码生成目标文本摘要。实验采用Rouge值作为摘要的评测指标，与其他方法进行的对比实验结果表明，所提方法所生成的文本摘要的准确率和流畅度更高。     

The issue of translation during thematic analysis in a tourism research context

This research note discusses issues with translation of non-English text during qualitative analysis in tourism research using examples from the newly emergent phenomenon of Chinese working holidaymakers in New Zealand. In particular, this note highlights an additional translation step in the thematic analysis process with non-English interview quotes and excerpts. This note argues the merit of researchers’ dual role as researcher/translator and discusses how researchers can undertake translation in cross-language research to maintain the rigour of qualitative tourism research.     

Racism in tourism reviews

Racism is increasingly recognised as a key driver of unfair inequalities in power, resources and opportunities across racial groups. A comprehensive understanding of racism is beneficial to activist groups, policymakers and governments. Traditional approaches, such as surveys and interviews, are usually time-consuming and inefficient in capturing the occurrence of large-scale racism. In this study, we utilise routinely collected data available on tourism websites to assess self-reported racism in the tourism domain. We present a data acquisition procedure that collects racism-related reviews from the Internet at the global scale and then utilise statistics and natural language processing techniques to analyse and explore racism in terms of its tendency, distribution, semantics and characteristics. The effectiveness of the proposed method is demonstrated in a case study, in which we acquire racism-related data at the global scale and validate the impact of racial discrimination on tourists’ experience.     

Social media bots and stock markets

This study examines the link between information spread by social media bots and stock trading. Based on a large sample of tweets mentioning 55 companies in the FTSE 100 composites, we find significant relations between bot tweets and stock returns, volatility, and trading volume at both daily and intraday levels. These results are also confirmed by an event study of stock response following abnormal increases in the volume of tweets. The findings are robust to various specifications, including controlling for traditional news channel, alternative measures of volatility, information flows in pretrading hours, and different measures of sentiment.     

广告语篇内部结构的人际意义思考

广告的主要功能是传递人际意义,它的表现形式多种多样。广告内部结构通过小句之间的衔接和广告语篇的总体结构来实现人际意义。     

语用知识在语篇教学中的运用

社会文化、语境直接影响着语言理解。教师应通过文化导入和语用分析,帮助学生培养文化意识和语境意识,以提高语言理解能力。     

新编英语教程中的美学欣赏

李观仪教授主编的《新编英语教程》彰显强烈的审美特征。教学中,应挖掘教材的审美意义,师生共同欣赏篇章的艺术性、语言的形式美、字里行间的意蕴美,充分理解教材的美学内涵,以达到心灵的升华。     

基于LDA主题模型的专利文本分析应用研究

为了解决运用传统的专利文本分析方法中出现的分类粗糙、科学性不强等问题,提出使用基于Latent Dirichlet Allocation(LDA)主题模型的专利文本分析方法。以我国转基因玉米育种领域专利文本为研究对象,对专利文本主题进行划分。通过实验表明LDA主题模型对专利文本的划分和热门领域的分类准确、有效。并得出结论:对专利文本使用LDA主题模型建模可以实现对专利文本的分类,可以实现对热门领域主题分类、子领域细分,并对未来发展态势给出意见。