Socialabs brings multiple forms of social-media analysis together, including topic modeling, network analysis, influencer discovery, sentiment and emotion analysis, and a chatbot for conversational exploration.
Visual notes
Inside the project.
Socialabs analytics dashboard with topic and network visualizationsSocialabs team at APICTA Brunei 2024
02 / Approach
How it is put together.
01
Topic modeling
Explore recurring topics in X/Twitter content to help make large collections of posts more interpretable.
02
Network and influencer analysis
Use network analysis and influencer discovery to explore relationships and identify influential accounts.
03
Sentiment and emotion analysis
Analyze the expressed sentiment and emotions in social-media content as part of the analytics experience.
04
Conversational exploration
A chatbot provides another way to explore social-media insights through natural-language interaction.
03 / Outcomes
Signals of impact.
Figures and recognition are presented as recorded in the project information; measurement details should be included where available.
10.
User interviews
The project brief records 10 user interviews as part of its research.
40%.
Reported workflow improvement
The portfolio records a 40% improvement; the measurement method should be documented alongside this figure when available.
Finalist.
APICTA Awards 2024
Business Services & R&D category, representing Indonesia.
Project takeaway
What came out of it.
Socialabs reached the APICTA Awards 2024 final in Business Services & R&D. The project brief also records 10 user interviews and a reported 40% workflow improvement.
