Dobong-gu 'Hyean' Big Data Analysis of the Past 7 Years?

Published 30 Jun.2021 06:30(KST)

Dobong-gu Identifies Keyword Sentiment Differences Between 5th and 7th Elected Terms Using Ministry of Interior's Big Data Analysis System 'Hyean'... Comparative Analysis of External Data Keywords (News, SNS, Blogs) from 2014-2015 1st Year of 5th Term and 2020-2021 3rd Year of 7th Term, Exemplary Scientific Administration Using Big Data... Administrative Keywords Surge, Positive Word Ratio Increases Over 25%, Result of Continuous Promotional Efforts

Dobong-gu Mayor Lee Dong-jin is demonstrating the 'Open Digital Mayor's Office.' (February 2, 2021)

Screenshot of the main page of Dobong-gu DBDBMAP website

[Asia Economy Reporter Jongil Park] Dobong-gu (Mayor Dongjin Lee), which is expanding its horizon from a bedroom town at the edge of Seoul to a new economic hub in the northeast. How do outsiders perceive these changes in Dobong, and where is Dobong headed?

In June 2021, Dobong-gu utilized the Ministry of the Interior and Safety’s National Intelligence Service's 'Hyean System - Big Data Common Platform (Social Analysis)' to empirically analyze Dobong’s image as seen through the media and social networks, tracking the changes over the past seven years.

For this, Dobong-gu set the analysis keyword as ‘Dobong’ and compared search data from news, blogs, and Twitter during the first year of the 5th local government term (July 1, 2014 to June 30, 2015) and the first year of the 7th local government term (July 1, 2020 to June 14, 2021). A total of 97,569 data points were collected: 30,515 from the 5th term’s first year and 67,054 from the 7th term’s first year.

Keywords from 2014-2015 mainly reflected general geographic and lifestyle issues. Words related to major tourist spots, hiking, and transportation such as Banghak Intersection, rear-end collision, Dobongsan Station, Madang Rock, Jawoon Peak, Bukhansan, and Ui Rock predominated.

What about the keywords from 2020-2021?

Amid the influence of COVID-19, many general terms related to the pandemic were identified, alongside meaningful administrative terms related to community development and various external evaluations, such as library, information guidance, cultural and sports promotion, and exemplary cases of sincere evaluation.

The difference becomes even more pronounced when focusing solely on the media sector. In the earlier comparison year, media results related to incidents and accidents such as property damage, police officials, and assault were found, whereas in the later comparison year, words central to the district’s major projects like sustainable development, cultural infrastructure, excellent villages, and DB appeared predominantly in the media.

Dobong-gu explains these results as the ripple effect of continuous administrative efforts targeting the media. This indicates that the district’s messages are being conveyed to residents through the media and underscores the need for ongoing administrative and sustained media promotion.

Meanwhile, the proportion of positive words related to Dobong also increased. Among the keywords searched, the share of positive words was 46.2% in 2014-2015, rising to 71.9% in 2020-2021, showing an increase of over 25%.

This overall decrease in neutral and negative opinions about Dobong indicates that the topic is generally described with positive terms.

Dobong-gu plans to share these analysis results with all department staff to reaffirm the importance of promotion and intends to use periodic trend analyses based on big data as policy indicators.

Mayor Dongjin Lee of Dobong-gu said, “Our district does not see big data as something distant but has built a data lifestyle map called ‘DBDB Map’ that is open to residents. I also receive great help in policy decisions through the ‘Digital Mayor’s Office,’ which comprehensively covers Dobong-gu’s administrative information.”

He added, “This media big data analysis was conducted to understand how Dobong-gu’s image is perceived by residents and how much it has changed over time, to predict and prepare for the future. We will strive to become a leading local government in scientific administration by utilizing big data across all administrative areas.”