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Feature Extraction of Format of Corporate Social Responsibility Reports

Du, Lanmei (2022-07-13)

Feature Extraction of Format of Corporate Social Responsibility Reports

Du, Lanmei
(13.07.2022)
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522588_Lanmei_Du_1.pdf (1.316Mb)
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Julkaisu on tekijänoikeussäännösten alainen. Teosta voi lukea ja tulostaa henkilökohtaista käyttöä varten. Käyttö kaupallisiin tarkoituksiin on kielletty.
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Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2022080552948
Tiivistelmä
As an important bridge that transmits signals to the market, the corporate social responsibility report has been an important theme among stakeholders in evaluating organizational efficiency and performance. Its quality will affect the decision-making and judgment of investors, thereby affecting the response of the capital market.
In recent years, social responsibility reports have shown a trend of rich pictures and diverse text designs. On the one hand, social responsibility reports composed of black and white text can hardly meet the information needs of different readers. On the other hand, reports with rich pictures and various text designs can give information users a better reading experience.
However, due to the lack of uniform standards on the format of social responsibility reports, there is still a lot of space for the research on the format of social responsibility reports. This thesis explores how to effectively extract the features of social responsibility reports, so as to further explore the feature dimension, set feature indicators and analyse feature data.
Firstly, existing studies have proved that the format of the social responsibility report has an impact on the stakeholder's impression management, and the way of impression management is mostly based on the design of picture arrangement, text arrangement and page structure.
Secondly, the guidelines of the Shanghai Stock Exchange (the guidelines on social responsibility reports issued by the Shanghai Stock Exchange), the GRI (Global Reporting Initiative) standards take the format as an important criterion for evaluating the quality of social responsibility reports. Based on this, interviews were conducted with five researchers in the field of social responsibility.
Then, a social responsibility report was taken as an example to conceptualize the feature annotation to get the two-dimensional data. Since CSR has different year data, different page data and different feature data, therefore, this thesis used Seaborn graph software to describe the three-dimension feature data.
Finally, this thesis takes a report of Vanke as an example to compare the social responsibility reports of Vanke in different years, and the comparison of the layout format of the real estate industry by Vanke and the financial industry by PingAn Bank.
Kokoelmat
  • Pro gradu -tutkielmat ja diplomityöt sekä syventävien opintojen opinnäytetyöt (kokotekstit) [9076]

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