Text Mining Improves Hong Kong Government’s Ability to Anticipate and Address Public Complaints

Text Mining Improves Hong Kong Government’s Ability to Anticipate and Address Public Complaints

The 1823 Call Centre of the Hong Kong government’s Efficiency Unit acts as a single point of contact for handling public inquiries and complaints on behalf of many government departments. 1823 operates round-the-clock, including during Sundays and public holidays. Each year, it answers about 2.65 million calls and 98,000 e-mails, including inquiries, suggestions, and complaints. “Having received so many calls and e-mails, we gather substantial volumes of data. The next step is to make sense of the data,” says the Efficiency Unit’s assistant director, W. F. Yuk. “Now, with SAS text mining technologies, we can obtain deep insights through uncovering the hidden relationship between words and sentences of complaints information, spot emerging trends and public concerns, and produce high-quality complaints intelligence for the departments we serve.”

Building a “Complaints Intelligence System”

The Efficiency Unit aims to be the preferred consulting partner for all government bureaus and departments and to advance the delivery of world-class public services to the people of Hong Kong. The Unit launched the 1823 Call Centre in 2001. One of 1823’s main functions is handling complaints—10 percent of the calls received last year were complaints. The Efficiency Unit recognized that there are social messages hidden in the complaints data, which provides important feedback on public service and highlights opportunities for service improvement. Rather than simply handling calls and e-mails, the Unit seeks to use the complaints information collected to gain a better understanding of daily issues for the public.

“We previously compiled some reports on complaint statistics for reference by government departments,” says Yuk. “However, through ‘eyeball’ observations, it was absolutely impossible to effectively reveal new or more complex potential public issues and identify their root causes, as most of the complaints were recorded in unstructured textual format,” says Yuk. Aiming to build a platform, called the Complaints Intelligence System, the Unit required a robust and powerful suite of textprocessing and mining solutions that could uncover the trends, patterns, and relationships inherent in the complaints.

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