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  1. R.U GOBITHAASAN, NUR FARHANA SYAHIRA CHE HAMID
    MyJurnal
    Sentiment analysis is a field of research that has a significant impact on today’s nations, politics and businesses. It is an algorithmic process to comprehend the opinions of a given subject based on the Natural Language Processing (NLP) methodologies. It has received much attention in recent years and is proven vital in various fields, e.g., online product reviews and social media analysis (Twitter, Facebook, etc.). This paper reports the outcome of sentiment analysis to investigate people’s acceptance of Pakatan Harapan, as the new Malaysian government, spearheaded by Tun Dr. Mahathir Mohamad and Dr. Wan Azizah, with an influence of Dato Seri Anwar Ibrahim. The objective is to classify tweets into three types of sentiments; positive, neutral and negative using Naïve Bayes method which is readily available in Python. The first step is tweets extraction for a month (March to April 2019) using search queries: {Pakatan Harapan, Mahathir, Anwar Ibrahim, Wan Azizah}. It is followed by tweets wrangling using NLP library and lastly output visualization in the form of a word cloud. A word cloud is a visual representation of text data with various font sizes depending on its probabilities. Final results showed that the tweets related to new government consist of neutral sentiment (41%) followed by positive sentiment (30%) and negative sentiment (29%). Malaysians do prefer the new government. However careful mitigation steps must be crafted to overcome controversial issues such as the ‘Rome Statute’ to avoid negative digital footprint, hence winning the Malaysians’ heart.
    Matched MeSH terms: Rome
  2. Chuah KH, Beh KH, Mahamad Rappek NA, Mahadeva S
    J Dig Dis, 2021 Mar;22(3):159-166.
    PMID: 33595169 DOI: 10.1111/1751-2980.12975
    OBJECTIVE: To explore the differences in frequency and epidemiology of functional gastrointestinal disorders (FGIDs) in a primary care setting, and to examine the health-related quality of life (HRQOL) and healthcare utilization of FGID patients based on the Rome III and Rome IV criteria.

    METHODS: A cross-sectional study of consecutive adults in a primary healthcare setting was conducted. Differences in epidemiology, and HRQOL of common FGIDs (functional dyspepsia [FD], irritable bowel syndrome [IBS], functional diarrhea, functional constipation [FC]) between the Rome III and IV criteria were explored.

    RESULTS: Among a total of 1002 subjects recruited, the frequency of common FGIDs was 20.7% and 20.9% among subjects based on the Rome III and Rome IV criteria, respectively. The frequency of IBS reduced from 4.0% (Rome III) to 0.8% (Rome IV), while that of functional diarrhea increased from 1.2% (Rome III) to 3.3% (Rome IV). In contrast, there was no significant change in the frequency of FD (7.5% [Rome III] vs 7.6% [Rome IV]) and FC (10.5% [Rome III] vs 11.7% [Rome IV]). Most of the Rome III IBS subjects (52.5%, n = 21) who did not meet Rome IV IBS criteria, fulfilled the criteria for FC, functional diarrhea, FD, or overlap syndrome. Subjects with all FGIDs, regardless of criteria, had more healthcare utilization and lower HRQOL compared to non-FGID controls.

    CONCLUSIONS: The Rome IV criteria alter the frequency of IBS and functional diarrhea, but not FD and FC, when compared to the Rome III criteria. Regardless of criteria, FGIDs had a significant impact on healthcare burden and HRQOL.

    Matched MeSH terms: Rome; Irritable Bowel Syndrome
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