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The hottest social and lifestyle feed in Hong Kong
The hottest social feed in Hong Kong
Data as at 06/06/2023 15:00
1197
荃灣躁漢揮菜刀兇菜檔職員 兩警手按槍袋將其制服
恐嚇案
荃灣
蔡玉玲查冊案 終審庭今裁定上訴得直
蔡玉玲
查冊
258
李慧詩退役
李慧詩
退役
8027
The hottest lifestyle feed in Hong Kong
Data as at 06/06/2023 15:00
魏浚笙分享照片
Wisers Rankings
Big data and AI-powered analysis in multiple perspectives
魏浚笙
生活
1609
山水盈屋苑嚴重滲水
山水盈
滲水
73
林芊妤分享相片
林芊妤
生活
35K
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Based on Wisers’ 20+ years of omni-media big data accumulation, scientific modeling and advanced artificial intelligence technology Listen to the voice of Hong Kong people from an all-round, objective and neutral perspective
Omni-media analysis
1,910,035,665
data volume
About
Hong Kong social media data include online posts, comments and engagement (daily data collection)
Wisers Big Data In-depth Analysis
Interpret the voice of Hong Kong people with the insights provided by our data scientists and analysts
The Government launched a new round of Anti-Epidemic Fund, a whole-day dine-in ban, social distancing rules, and a voluntary universal virus test programme to cope with the pandemic, which has affected everyone’s daily life. The impacts of these policies were felt across all the seven key aspects of life, covering clothing, dining, accommodation, transportation, work, study and entertainment. Which issues were of the greatest concern to citizens? What struck them the most?
Since the outbreak, the public have focused on issues ranging from border closure to the influx of students returning from overseas, from sharing the latest news about face mask supply to supporting local mask production, from home quarantine to city-wide social distancing measures. What were the most well received and least well received issue for Hong Kong people? The government successfully proposed three rounds of anti-epidemic relief package with record amount. However, the reception was mixed at best. How should genuine public opinion be interpreted and identified?
Within the data period from 1st January to 14th February, Wisers' research team combined big data computing models and artificial intelligence text analysis technology to analyze more than 280,000 epidemic-related posts, more than 10.92 million Internet users' comments, and nearly 3.4 billion engagements among netizens. The research team compared the degree of netizens concern reflected by big data with the number of confirmed cases every day. We discovered that the two are not neces-sarily proportional to each other, reflecting there were other factors that cause greater public concern and affect the mainstream mood than confirmed cases.
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