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Recent research suggests that advocacy groups use a variety of narrative strategies to achieve their policy goals on social media. However, previous studies have not thoroughly investigated about the relational and dynamic nature within policy narratives, and little research has been conducted to compare the narrative strategies employed by competing advocacy groups in the U.S. oil and gas policy subsystem. Applying a text mining and network approach, this study uses the Narrative Policy Framework (NPF) to examine how advocacy groups use narrative strategies to support or oppose oil and gas development through Twitter from 2009 to 2023. Structural topic modeling (STM) reveals six prominent themes, which I organize into a taxonomy of narrative strategies and show how they correlate with different groups and how they change over time. While the pro-oil and gas groups use a logic of job creation, energy security, energy independence, and energy sufficiency to emphasize policy benefits, the anti-oil and gas groups focus on the policy costs including air pollution, health threats, climate change, and wildlife devastation. Furthermore, a graph of potential characters’ relationships is presented based on social network analysis (SNA), demonstrating that the pro-oil and gas advocacy groups tend to maintain higher values of degree centrality. This paper suggests a more holistic and mixed-methods approach to refining the NPF and highlights the role of networks in advancing policy agendas.