It can be difficult to assess and improve the health of a company. Company leaders need visibility into employee engagement, insight to focus on what is most important, and guidance to take effective action. To this end, web-based computing platforms exist to solicit and obtain comments from employees. These platforms allow the company to present prompts for comments to employees in a web-based user interface. Using the web-based user interface, the employees can provide anonymous comments about the company and the employment experience in a free-form text format. […]companies would appreciate solutions that help them more quickly identify toxic comments among potentially tens or hundreds of thousands of comments submitted by employees.
By toxic content, the method refers to comments that are rude, disrespectful, threatening, obscene, insulting, and contain identity-based hate.
If the method will see the light in final products such as Microsoft Teams or related apps, it will greatly contribute to a healthier work environment.
How will a comment/remark be flagged as toxic?
As the description of the patent shows, one solution would be to train a deep machine learning classifier to classify comments as to toxicity.
The level of toxicity for a word, comment, or remark will be established given the frequency of use under certain circumstances.
[…]the toxic keywords are determined based on comparing term frequencies of the keywords in a set of example toxic interpersonal electronic communications against term frequencies of the keywords in a set of example non-toxic interpersonal electronic communications. A keyword is determined as indicative of toxic content if its term frequency in the set of toxic examples is more than a threshold number of times more than its term frequency in the set of non-toxic examples.
How often a keyword can appear before it’s considered toxic, is probably a detail that each company should establish.
Although, as the authors of the patent mention, establishing what is toxic or not might consistently vary from one enterprise to another.
At any stage of the process, users can opt in or out of the process. Also, personally identifiable information when using this method may be removed, if desired.
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