Characterizing Twitter Influencers in Radiation Oncology

Area of Science:

• Social Media Analysis
• Network Science
• Radiation Oncology

Background:

• The landscape of virtual discourse and influential entities in radiation oncology social media is not well understood.
• Characterizing these online communities is crucial for understanding information dissemination in the field.

Purpose of the Study:

• To analyze the structure of virtual discourse on Twitter within radiation oncology.
• To identify and categorize influential users in the #radonc community.

Main Methods:

• A year-long prospective sampling of tweets using the #radonc hashtag.
• Community detection algorithms (Clauset-Newman-Moore) to group Twitter handles.
• Betweenness centrality to identify top influencers and regression analysis to predict influence.

Main Results:

• The #radonc network functions as a hub-and-spoke broadcast model.
• Professional societies were the most influential category, followed by industry and then individuals.
• Male, US-based academic radiation oncologists were significant predictors of higher influence.

Conclusions:

• Influential Twitter users in radiation oncology are diverse, but male North American academic radiation oncologists hold prominent positions.
• Regular network analysis is needed to monitor influential voices and ensure social media effectively contributes to radiation oncology.