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This study is motivated to provide a theoretically informed, data-driven assessment of the consequences associated with the participation of non-human bots in social accountability movements; specifically, the anti-inequality/anti-corporate #OccupyWallStreet conversation stream on Twitter.

A latent Dirichlet allocation (LDA) topic modeling approach as well as XGBoost machine learning algorithms are applied to a dataset of 9.2 million #OccupyWallStreet tweets in order to analyze not only how the speech patterns of bots differ from other participants but also how bot participation impacts the trajectory of the aggregate social accountability conversation stream. The authors consider two research questions: (1) do bots speak differently than non-bots and (2) does bot participation influence the conversation stream.

The results indicate that bots do speak differently than non-bots and that bots exert both weak form and strong form influence. Bots also steadily become more prevalent. At the same time, the results show that bots also learn from and adapt their speaking patterns to emphasize the topics that are important to non-bots and that non-bots continue to speak about their initial topics.

These findings help improve understanding of the consequences of bot participation within social media-based democratic dialogic processes. The analyses also raise important questions about the increasing importance of apparently nonhuman actors within different spheres of social life.

The current study is the first, to the authors’ knowledge, that uses a theoretically informed Big Data approach to simultaneously consider the micro details and aggregate consequences of bot participation within social media-based dialogic social accountability processes.

Corruption and dishonesty in the political and bureaucratic realms have impeded the ability of local governments to provide services and social justice in Nepali society. In light of this, the purpose of this research is to answer the key research question: what are the possibilities and limitations of local government in implementing constitutionally guaranteed rights in order to transform local communities?

This study gathered qualitative data from 14 local governments in seven provinces. A total of 56 in-depth interviews were held with elected representatives, political parties, and government officials at both the national and local levels. Both open-ended and open-structured questionnaires were employed for the interviews.

The results indicate that capacity is a major constraint for local governments, which should be addressed to achieve successful local governance, inclusive citizen engagement, and strong technical, administrative and fiscal capabilities. Lack of local autonomy, political conflict and social class differences, external engagement, and conservative hierarchic government bureaucracy are major hurdles to growing capacity.

This paper analyses the capacity of newly restructured local governments through qualitative approach. It attempts to understand to what extent the Nepali local governments are capable in delivering the services at the local level as closest unit of the citizens.