Corporate Social Responsibility Dictionary for Text Analytics (FREE) 

By Nadra Pencle and Irina Mălăescu (2016)


The Corporate Social Responsibility content analytic dictionary was developed by Nadra Pencle and Irina Malaescu (2016) and used to predict various components of IPO pricings. The authors analyzed the prospectus of U.S. IPOs from 2011-2013, in part, because the IPO process has the potential to convey usable information that can signal business plans and managers’ level of confidence, as well as potential problems in their businesses. (Loughran and MacDonald 2016) Therefore, it can be reasoned that despite the lack of regulatory requirements, a company entering into the public equity market and wishing to signal to potential investors its stance on CSR orientation may do so using a more detailed CSR disclosure in its prospectus than it might otherwise. Pencle and Maleaescu (2016) developed a multi-dimensional corporate social responsibility words (CSRW) dictionary with four dimensions; Social and Community, Human Resources, Environment and Human Rights.

In line with the guidelines by Short, Broberg, Cogliser, and Brigham (2010) and Kenny et al (2013) both a deductive and inductive wordlist was generated using related CSR literature. With the help of qualitative analysis and content analysis software tools the authors produced an inductive wordlist of 1,002 words. To validate the final wordlists three judges with significant expertise in the field of CSR were enlisted. The final dictionary is comprised of words on which consensus was reached.


Example of words

Number of words


Adopted Child, Health Benefits, Educate, Employed, Discriminatory, etc…


Human Rights

Aboriginals, Fairness, Oppressive Regime, Same Sex, Religious Diversities, etc…



Acid Rain, Conservation, Fossils, Green Engineering, Renewable Energy, etc..


Social and Community

Transparent, Foodbank, Indigenous People, Social Issue, etc…


To test the hypothesis the authors used a variety of models and used several independent variables to account for the non-hypothesized effects on each of the hypothesized dependent variables. The resulting dictionary provides a new measure of CSR that can be generalized to other text documents released by a corporation. The authors note that since each research project is different, future researchers using the dictionary may make refinements and extensions based on their specific research.

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To find out how Provalis Research text analytics tools have been used for Corporate Social Responsibility research, read our white paper Corporate Social Responsibility

Main Reference (to be cited in all publications that use it). Nadra Pencle and Irina Mălăescu (2016) What’s in the Words? Development and Validation of a Multidimensional Dictionary for CSR and Application Using Prospectuses. Journal of Emerging Technologies in Accounting: Fall 2016, Vol. 13, No. 2, pp. 109-127.