Predicting and Identifying behavioral analysis in social media using big data analytics is exceptionally repetitive. Since data in motion are difficult to capture and process with existing innovation. In spite of the fact that there are numerous frameworks that have executed for user behavior analysis, it’s as yet an upcoming and unexplored market that has more prominent potential for better advancements. So with the help of Hadoop framework, a new approach of designing a communal framework is proposed and it’s used for predicting and identifying user’s behavioral analysis in a community. The proposed work can be applied in the community-based environment where the prediction and identification of user behavior analysis has to be made with the semantic web approach. In addition to that, a suitable model for the communally accountable software objects where these objects would observe online communal network information is designed. Further, these objects in online communal network, assess them from the viewpoint of communally accountable performance based on the relation modeling conceptions. The location of communally accountable mediators is grounded in diverse methods. Diverse illustrations are grabbed from the analysis with microblog assessments, community semantic web, higher relations for communal web and social network sourced big information assessments. In the proposed framework, the analysis is based on the assessment/observation of the communally accountable performance of the communal media big data and design of higher-level relations as the model for the above mentioned assessments.

中文翻译：

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公共软件框架设计：基于关系建模的评估

使用大数据分析预测和识别社交媒体中的行为分析非常重复。由于现有创新难以捕获和处理动态数据。尽管有许多框架可以执行用户行为分析，但它仍然是一个即将到来的未开发市场，具有更显着的改进潜力。因此，在Hadoop框架的帮助下，提出了一种设计社区框架的新方法，并将其用于预测和识别社区中用户的行为分析。所提出的工作可以应用于基于社区的环境中，其中必须使用语义网络方法进行用户行为分析的预测和识别。在此之上，为共同负责的软件对象设计了一个合适的模型，这些对象将观察在线公共网络信息。此外，在线公共网络中的这些对象，基于关系建模概念，从公共责任绩效的角度对其进行评估。对社区负责的调解员的位置以多种方法为基础。从微博评估、社区语义网、公共网的高级关系和社交网络来源的大信息评估的分析中获取了不同的插图。在提议的框架中，分析基于对公共媒体大数据的公共责任绩效的评估/观察和高层关系的设计，作为上述评估的模型。