Privacy Protection in COVID Data Tracking: Textual Analysis of the Literature

The literary review presented in the following paper aims to analyze the tracking tools used in different countries during the period of the COVID-19 pandemic. Tracking apps that have been adopted in many countries to collect data in a homogeneous and immediate way have made up for the difficulty of collecting data and standardizing evaluation criteria. However, the regulation on the protection of personal data in the health sector and the adoption of the new General Data Protection Regulation in European countries has placed a strong limitation on their use. This has not been the case in non-European countries, where monitoring methodologies have become widespread. The textual analysis presented is based on co-occurrence and multiple correspondence analysis to show the contact tracing methods adopted in different countries in the pandemic period by relating them to the issue of privacy. It also analyzed the possibility of applying Blockchain technology in applications for tracking contagions from COVID-19 and managing health data to provide a high level of security and transparency, including through anonymization, thus increasing user trust in using the apps.

Tone of language,financial disclosure,and earnings management:a textual analysis of form 20-F

This study investigates the relationship between the tone of financial disclosures and managers’earnings management behavior using Form 20-F filings of Chinese firms listed in the U.S.during 2002–2014.The results show that the proportion of positive,uncertain,or modal words used in financial disclosures is positively related to corporate earnings management,implying that managers attempt to conceal earnings management behavior by manipulating the tone of their financial reports.In addition,robustness tests are conducted using an alternative proxy for earnings management that considers the effects of the financial crisis and separately examines the information and non-information technology industries.The results suggest that the tone used in financial disclosures has informative value,and textual analysis can be an effective tool for identifying earnings management.

Does investor communication improve corporate social responsibility?A machine learning-based textual analysis

In this study,we take a machine learning-based approach to measure institutional investor attention to corporate social responsibility(CSR)issues when communicating with firms during site visits.We find that institutional investors can effectively enhance CSR performance through CSR-related communication.This effect remains robust to various checks and is more pronounced for non-state-owned enterprises and firms with lower levels of institutional ownership and in periods following the issuance of Green Investment Guidelines.We also identify information asymmetry and financing constraints as the two mechanisms underlying this effect.Overall,our findings highlight the importance of private interactions between management and institutional investors in promoting CSR.

Multimodal sentiment analysis for social media contents during public emergencies

Purpose:Nowadays,public opinions during public emergencies involve not only textual contents but also contain images.However,the existing works mainly focus on textual contents and they do not provide a satisfactory accuracy of sentiment analysis,lacking the combination of multimodal contents.In this paper,we propose to combine texts and images generated in the social media to perform sentiment analysis.Design/methodology/approach:We propose a Deep Multimodal Fusion Model(DMFM),which combines textual and visual sentiment analysis.We first train word2vec model on a large-scale public emergency corpus to obtain semantic-rich word vectors as the input of textual sentiment analysis.BiLSTM is employed to generate encoded textual embeddings.To fully excavate visual information from images,a modified pretrained VGG16-based sentiment analysis network is used with the best-performed fine-tuning strategy.A multimodal fusion method is implemented to fuse textual and visual embeddings completely,producing predicted labels.Findings:We performed extensive experiments on Weibo and Twitter public emergency datasets,to evaluate the performance of our proposed model.Experimental results demonstrate that the DMFM provides higher accuracy compared with baseline models.The introduction of images can boost the performance of sentiment analysis during public emergencies.Research limitations:In the future,we will test our model in a wider dataset.We will also consider a better way to learn the multimodal fusion information.Practical implications:We build an efficient multimodal sentiment analysis model for the social media contents during public emergencies.Originality/value:We consider the images posted by online users during public emergencies on social platforms.The proposed method can present a novel scope for sentiment analysis during public emergencies and provide the decision support for the government when formulating policies in public emergencies.

Research on the Classification of Western Literary Criticism Under M. H. Abrams’Fourfold Model

This study explores the application of Abrams’Fourfold Model in the classification of Western literary criticism.Abrams’framework categorizes literary criticism into four fundamental elements:text,author,world,and audience.The text is viewed as an independent entity with intrinsic artistic value,necessitating a detailed analysis of its structure,style,themes,and symbols.Author study delves into the creator’s life and socio-cultural context,often to uncover the work’s deeper meanings.Contextual study situates the work within its historical and social milieu,examining its reflection of or response to societal norms and events.Audience response analysis considers the diverse interpretations shaped by readers’backgrounds,emphasizing the reader’s role in constructing the work’s meaning.The study concludes that Abrams’Fourfold Model offers a comprehensive and flexible analytical tool,enabling critics to engage with literary works from multiple perspectives,thereby enriching the understanding of literary complexity and diversity.

Transitivity System and Power Relationship-Analysis of William Faulkner＇ s A Rose for Emily

This paper explores how transitivity system functions in the novel A Rose for Emily, especially how it builds up and reflects the suppression on Emily by Emily's father, who represents the patriarchal value system and by the citizens who represents the southern traditional value system. This paper also elaborates how Emily appeared to be powerless and was dominated by the two groups of power, and how her humanity and emotions were suppressed in the conflict of the two categories of power.

The traumatic narratives of sexuality in Chinese writer Shao-Lin Chu’s trilogy

This paper explores the narratives of the Chinese woman novelist Shao-Lin Chu’s trilogy to see how the problem of female sexuality and resistance to parental wedlock tragedy becomes a traumatic experience.The traumatic symptoms in the narratives are taken as Peircean signs for tracing the negative influences of traumatic experiences on the formation of personal identity and the associated depressive disorder.The scenes portrayed in Chu’s traumatic narratives of female and male sexuality are implications and representations of how sexuality is conceptualized and confined by the traumatic events while backgrounded with regulations and restrictions of a traditional society.The stories of Chu’s female narrators reveal the persistent and resisting feminine power.This paper adopts the concept of feminist narrative to analyze the traumatic and sexual events in Chu’s trilogy.The decoding and re-encoding of resistance and sexuality in the traumatic narratives prove that the narratological textual analysis and semiotic reading strategy together offer a solid approach to the discovery of the persistent traumatic impacts of the secret veiled in the narratives and reveal the probable strength of compassion that has its roots derived from deplorable trauma but later transforms itself to stimulate a positive reconstruction of the traumatic survivors’identity.

Business and financial information integration and voluntary management earnings forecasts

In this study,the impact of business and financial information integration(BFⅡ)on the voluntary management earnings forecasts(VMEFs)of listed firms in China between 2008 and 2018 is investigated.Drawing on litigation cost and ability signaling theories,we find that the adoption of BFⅡencourages top managers to disclose VMEFs.BFⅡfirms are identified through the textual analysis of management discussion and analysis(MD&A)reports,and the empirical results indicate that BFⅡfirms have a higher probability and frequency of issuing VMEFs than non-BFⅡfirms.The results remain robust after we identify causality by applying a propensity score matching and difference-in-differences(PSM-DID)test and use an alternate measure of BFⅡ.Further tests show that BFⅡfirms issue more accurate VMEFs and are able to issue them at an earlier stage.We also find that the positive relationship between BFⅡand VMEFs is weakened if the media expresses concern about the uncertainty of BFⅡadoption.

Linguistic specificity and stock price synchronicity

Linguistic specificity effectively reduces barriers to information cognition,increasing the efficiency of information acquisition,integration and processing.Combining the psycholinguistics theory of the concreteness effect with assetpricing theory,we determine that linguistic specificity in the management discussion and analysis section of a firm’s annual reports is negatively associated with stock price synchronicity,particularly in firms with strong external information demand or insufficient information supply.Furthermore,only specificity of the review section leads to a reduction in stock price synchronicity.Mechanism tests show that specificity reduces information processing costs and enhances information credibility.Additionally,proprietary costs are an essential determinant of linguistic specificity adoption.Our findings suggest that linguistic specificity plays an essential role in improving market pricing efficiency.

Visual storytelling of Song Ci and the poets in the social–cultural context of Song dynasty

Song Ci is treasured in traditional Chinese culture,which indicates social and cultural evolution in ancient times.Despite the efforts by historians and litterateurs in investigating the characteristics of Song Ci,it is still unclear how to effectively distribute and promote Song Ci in the public sphere.The complexity and abstraction of Song Ci hamper the general public from closely reading,analyzing,and appreciating these excellent works.By means of a set of visual analysis methods,e.g.the spatiotemporal visualization,we exploit visual storytelling to explicitly present the latent and abstractive features of Song Ci.We apply straightway visual charts and lighten the burden of understanding the stories,in order to achieve an effective public distribution.The effectiveness and aesthetics of our work are demonstrated by a user study of three participants with different backgrounds.The result reveals that our story is effective in the distribution,understanding,and promotion of Song Ci。