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Uncovering underlying dynamics among competitors in the digital world
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Resumo(s)
This study explores the intricate web of competition in e-commerce, utilizing advanced
methods in natural language processing and machine learning. This analysis delves into
previously undiscovered competitor networks, deciphering apparent and concealed competition
using advanced techniques such as Word2Vec and Graph Neural Networks. The research
redefines competitor identification in the digital era, emphasizing the importance of search
engine visibility. Leveraging Minimum Spanning Trees (MSTs) and network analysis, it offers
insights into digital competition dynamics. Traditional methods fall short in capturing this
complexity, necessitating a multi-step analytical framework. Findings reveal a hierarchical
relationship among competitors, at the same time providing insight into competition intensity
and connectivity. The analysis uncovers both direct and indirect competitors, enabling
businesses to refine their strategies based on semantic analysis to improve their positioning
across search engine rankings.
Descrição
Palavras-chave
Competition Company embeddings Representation learning Minimum spanning tree