How well is COVID

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How often do you use your nose/face mask?

The remaining 14-no attributes is prepared in an Attribute-Relation File Format (arff) for the REPTree machine learning phase described in section C. The description of the data attributes is as presented in Table 1 indicating the data type attributes.

B. Data Preprocessing This study applies preprocessing tasks to remove irrelevant contents, as proposed in [21] through the following steps: 1) Transformations: Including conversion of SN 15 opinion to lower case 2) Noise Removal: Elimination of punctuations, white spaces etc. 3) Tokenization: Includes tokenization of texts with Regexp approach. A uni-gram approach of word-tokenization is implemented on the opinions. 4) Filtering: Exclusion of stop words including articles, conjunctions, and prepositions that do not carry enough discriminative content needed for the opinion-mining task.

Fig. 1. Proposed study framework

Table 1. Nature of dataset attribute S/N Questions/Attribute Attribute_id Response options Arff response_id 1. Staff Category s_cadre Teaching; Hostel porter; NonTeaching; Medical Staff TS;HP;NT;MS

2. How often do you use your nose/face mask?

3. What is your salary level? mask_wearing Always-OftenSometimesRarely-Never staff_cat Below #120,000; #120,000 and above M-A;M-O;MS;M-R;M-N

SS; JS

4. Have you had COVID19 test and or vaccination before? 5. How well is COVID19 precautions being handled in your College?

6. How well are your students complying with COVID-19 safety measures? covid_test Yes; No Yes; No

college_handling Not at all satisfied; slightly satisfied; moderately satisfied; very satisfied; completely satisfied std_compl Not at all compliant; slightly compliant; moderately compliant; very compliant; extremely CH-1;CH-2;CH3;CH-4;CH-5

CC-1;CC-2;CC3;CC-4;CC-5