Tag Cloud Visualization Integrated with Dimensionality Reduction for Conceptualizing Communication Behavioral Data

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Abstract
Public relations (PR) aims to establish positive relationships of company-customer and government-citizen. PR researchers and scholars achieve this by analyzing communication behavioral data, which encompasses the public’s experiences in consumption, policy, and governance. However, labeling this data for analysis in PR is costly and complex, primarily due to its multi-label and the need for human judgment based on the Organization-Public Relationship Assessment (OPRA) concepts. Consequently, these problems limit the development of automated labeling models because more training data is needed for fine-tuning. In this paper, we propose a novel tag cloud visualization integrated with dimensionality reduction for conceptualizing communication behavioral data to address limitations in PR. We use attention-based embedding and dimensionality reduction to visualize the public’s experience as a scatter plot according to OPRA concepts. Additionally, we provide PR researchers and scholars with clues for multi-labeling by combining the tag cloud using Bag of Words (BoW) in a scatter plot. We evaluate our proposed interactive visualization through a case study and feedback from two PR researchers.

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