Accurate user identification serves as the cornerstone for demand recognition in precision marketing. Previous studies have overlooked the distorting influence of disinformation in online environments. This study develops an innovative user positioning framework that explicitly accounts for disinformation interference.
The proposed methodology employs a three-stage analytical process: First, advanced semantic analysis techniques identify and filter disinformation. Second, high-dimensional cluster analysis categorizes users through K-means optimization. Finally, a multidimensional integration of demographic attributes and behavioral preferences enables precise repositioning of high-impact users.
The framework demonstrates (1) significant improvement in disinformation detection accuracy through semantic analysis, (2) enhanced clustering purity in user segmentation, and (3) more reliable identification of high-impact users through multidimensional feature integration.
This study proposes a new method of high-impact user positioning by identifying the convoluting effect of disinformation on internet consumer communities.
