This project was a collaborative effort to create a social listening website focused on K-Pop, K-Movies, and K-Dramas, presented as a single-page website. The objective was to visualize social media data related to the Korean entertainment industry, tracking positive and negative sentiments around various topics and keywords without relying on a back-end infrastructure for data processing.

Process

Design Process

This project is one of those very rare projects where requirements were quite precise and the client had already decided which data visualization charts they want to be featured in the website. Our job in the design part is mostly to decide the key visual and, along the way, rearranging how the data visualizations should be presented based on the actual relations of each data sets. For key visual, we proposed a light theme with red and blue(a colors of Korean flag, and also popular colors combination in Korean infographics design) with photo collages of K-wave culture elements. The color blue and red also represent positive and negative sentiments in half of the data visualization charts.

Originally this website was intended to be a single page website with 8 consecutive topics under the same global navigation, but upon inspecting real data set, we decided to divide this website into 3 parts under 3 global navigations of their own as the time period of data collected from their social listening platform aren’t quite the same. Users will see these 3 parts as following;

Sentiments towards the popular keywords and the keywords’ relations
Sentiments and trends of each K-wave topics
Ontology of popular keywords

The background colors also change as users navigate between these 3 parts, adding a transition for better understanding and also to enhance experience navigating through this single page.

Data Process

Initiation: Boonme Lab sets out to create a social listening website for K-Pop, K-Movies, and K-Dramas, designed as a single-page application.
Challenge Identification: The major challenge was to manage data processing and visualization without a back-end, necessitating innovative solutions.
Decision on Data Processing: The team weighed options between front-end data processing and using pre-computed indexed files to ease computational load.
Collaboration for Efficiency: Data and front-end teams collaborated to develop efficient query functions, adjusting roles to enhance project workflow.
Implementation: A balanced approach was chosen, involving data compression and weekly indexed files, to minimize front-end processing demands.

Challenge

Design Challenge

To be honest, the challenge of this project doesn’t exactly lie in design part itself. Before starting the project, the main challenge was probably the lack of understanding what ‘Hallyu’ is, as our team members have a very limited understanding or interest in K-wave or Korean culture background. Just because our client had already decided which data visualization they wanted to use doesn’t mean we should follow them blindly without considering what project’s content is about. Preparing ourselves and researching the background of Hallyu helped our comprehension towards the project, gave us new idea inputs for next phase development(if we get a chance to), and those knowledge came in very handy in the QA process, especially on data display part.

Another challenge in this project is probably the communication and the language barrier. This is the first project where the responsible squad included a Korean member and also Korean clients, therefore we need to communicate in English as much as we could. there were naturally difficulties in the internal communications at first, but this project proved to be a start where we can see ourselves taking on more international projects with even more clients with diversities in the future.

Data Challenge

The project encountered three main challenges:

Deciding Data Processing Location: Choosing between processing data on the front-end or using pre-calculated index files to reduce front-end load. This decision balanced between computational efficiency and managing a potentially large number of index files.
Managing Increasing Data Volume: As more data is added over time, finding an efficient way to handle the increased computational load without significantly slowing down the user experience.
Collaboration on Query Functions: The data team had to work closely with the front-end team to develop query functions, a task typically outside their usual responsibilities, to ensure efficient data retrieval and processing on the website.

Development Challenge

The main development challenges for this project are:

Adopting ApexCharts as our new charting tool.
Managing the complexity of data and the integration of multiple datasets, which poses challenges in processing and calculations.

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