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The hottest social and lifestyle feed in Hong Kong
The hottest social feed in Hong Kong
Data as at 03/02/2023 15:00
68
全面通關 2.6起免配額免核酸
676
日本
香港
壽司郎
通關
壽司郎屁孩父親落淚致歉「他有在反省」
日本麥當勞暴雪夜營業 拍下神級唯美照
麥當勞
日本
3504
The hottest lifestyle feed in Hong Kong
Data as at 03/02/2023 15:00
陳瑞輝分享照片
Wisers Rankings
Big data and AI-powered analysis in multiple perspectives
陳瑞輝
生活
4564
送年糕畀女同事搞到女朋友嬲左我
年糕
賀年
50
林芊妤分享相片
林芊妤
生活
12K
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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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