This paper describes a sentiment analysis method to analyze comments polarity and to facilitate selected government agencies such as DepEd, DPWH, DILG, DND, DSWD, and DOH to describe quantitatively the opinions and comments of active users and citizens on social networks such as YouTube. The method used was from the latest comments from the first 100 were selected from each video to form the final datasets used in the study. The comments were extracted from 1450 videos and contain a total number of 14,506 posts. The objectives of the study were (1) to analyze the citizen's attitude among the six government agencies in the category of positive and negative polarity. (2) to utilized the results in developing a decision support system.
Purpose -The fire and crime incident datasets were requested and collected from two Philippine regional agencies (i.e., the Bureau of Fire Protection and the Philippine National Police). The datasets were used to initially analyze and map both fire and crime incidents within the province of Pampanga for a specific time frame.Method -Several data preparation, normalization, and data cleaning steps were implemented to properly map and identify patterns within the datasets.Results -The initial results also indicate the leading causes of fire and crimes are rubbish and acts against property. Fires mostly occur during the dry season in the province. Crime
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