Time Dependency, Data Flow, and Competitive Advantage
Ehsan Valavi, Joel Hestness, Marco Iansiti, Newsha Ardalani, Feng Zhu,, Karim R. Lakhani

TL;DR
This paper investigates how the value of user-generated data from Reddit varies over time across different topics and discusses implications for strategic data acquisition and competitive advantage.
Contribution
It introduces a method to measure the time-dependent relevance decay of data in different contexts and explores its impact on competitive strategies.
Findings
Different Reddit topics show varying rates of relevance decline.
Rapid data value decay favors strategies focusing on continuous data flow.
Engagement and user-base growth are crucial for maintaining competitive advantage.
Abstract
Data is fundamental to machine learning-based products and services and is considered strategic due to its externalities for businesses, governments, non-profits, and more generally for society. It is renowned that the value of organizations (businesses, government agencies and programs, and even industries) scales with the volume of available data. What is often less appreciated is that the data value in making useful organizational predictions will range widely and is prominently a function of data characteristics and underlying algorithms. In this research, our goal is to study how the value of data changes over time and how this change varies across contexts and business areas (e.g. next word prediction in the context of history, sports, politics). We focus on data from Reddit.com and compare the value's time-dependency across various Reddit topics (Subreddits). We make this…
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Taxonomy
TopicsBig Data and Business Intelligence · Data Visualization and Analytics · Advanced Text Analysis Techniques
