MAISoN 2019: The 3rd International Workshop on Mining Actionable Insights from Social Networks

Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval Pub Date : 2019-09-23 DOI:10.1145/3341981.3350529

Marcelo G. Armentano, E. Bagheri, Julia Kiseleva, Frank W. Takes

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Abstract

A lot of research in social network mining is concerned with theories and methodologies for community discovery, pattern detection and network evolution, as well as behavioural analysis and anomaly (misbehaviour) detection. The MAISoN workshop focuses on the use of social network data and methods for building predictive models that can be used to uncover hidden and unexpected aspects of user-generated content in order to extract actionable insights. The objective is to explore ways in which insights can be transformed into effective actions that can help organizations improve and refine their activities. Thus, the focus is on social network analysis and mining techniques for gaining actionable real-world insights. The 3rd International Workshop on Mining Actionable Insights from Social Networks (MAISoN 2019) was a half day workshop co-located with ICTIR 2019, the 5th ACM SIGIR International Conference on the Theory of Information Retrieval which took place from October 2 to 5, 2019 in Santa Clara, California, United States.

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MAISoN 2019:第三届从社交网络中挖掘可操作见解国际研讨会

社会网络挖掘的许多研究都涉及社区发现、模式检测和网络进化的理论和方法，以及行为分析和异常(不当行为)检测。MAISoN研讨会的重点是使用社交网络数据和方法来构建预测模型，这些模型可用于发现用户生成内容的隐藏和意想不到的方面，以提取可操作的见解。目标是探索将见解转化为有效行动的方法，从而帮助组织改进和完善其活动。因此，重点是社会网络分析和挖掘技术，以获得可操作的现实世界的见解。第三届从社交网络中挖掘可操作见解国际研讨会(MAISoN 2019)是一个为期半天的研讨会，与2019年10月2日至5日在美国加利福尼亚州圣克拉拉举行的第五届ACM信息检索理论国际会议ICTIR 2019共同举办。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval

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