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In open source software (OSS) communities, existing leadership indicators aredominantly measured by code contribution or community influence. Recent studieson emergent leadership shed light on additional dimensions such as intellectualstimulation in collaborative communications. To that end, this paper proposesan automated approach, named iLead, to mine communication styles and identifyemergent leadership behaviors in OSS communities, using issue comments data. Westart with the construction of 6 categories of leadership behaviors based onexisting leadership studies. Then, we manually label leadership behaviors in10,000 issue comments from 10 OSS projects, and extract 304 heuristiclinguistic patterns which represent different types of emergent leadershipbehaviors in flexible and concise manners. Next, an automated algorithm isdeveloped to merge and consolidate different pattern sets extracted frommultiple projects into a final pattern ranking list, which can be applied forthe automatic leadership identification. The evaluation results show that iLeadcan achieve a median precision of 0.82 and recall of 0.78, outperforming tenmachine/deep learning baselines. To demonstrate practical usefulness, we alsoconduct empirical analysis and human evaluation of the identified leadershipbehaviors from iLead. We argue that emergent leadership behaviors in issuediscussion should be taken into consideration to broaden existing OSSleadership viewpoints. Practical insights on community building and leadershipskill development are offered for OSS community and individual developers,respectively.

Identifying Emergent Leadership in OSS Projects Based on Communication Styles