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MODELING USER ATTITUDES TOWARD A TARGET FROM SOCIAL MEDIA

机译:建模用户对社交媒体目标的态度

摘要

Embodiments relate to user attitude modeling and behavior prediction for a social media network. One aspect includes collecting data relating to previously demonstrated sentiments, opinions, and actions attributed to network users toward a topic. Another aspect includes creating a model from the data, which includes factorizing the actions for behavior inference, factorizing auxiliary content from the network for opinion and sentiment inferences, and applying sentiment and opinion regularization to constrain user preferences on implicit topics to explicit sentiments and explicit opinions. Another aspect includes applying the model to a new user of the network with respect to the topic, and generating a prediction with respect to the user that includes predicting sentiment and opinion as a function of the auxiliary content and feature coefficients learned during a training process, and predicting a future action of the user as a function of the auxiliary content and latent profiles of the topic.
机译:实施例涉及用于社交媒体网络的用户态度建模和行为预测。一个方面包括收集与先前证明的归因于网络用户对主题的情绪,观点和动作有关的数据。另一个方面包括从数据创建模型,该模型包括分解行为推理的动作,分解来自网络的辅助内容以进行观点和情感推理,以及应用情感和观点正则化以将用户对隐式主题的偏好限制为显式情感和显式观点。另一方面包括相对于主题将模型应用于网络的新用户,以及针对用户生成预测,该预测包括根据在训练过程中学习到的辅助内容和特征系数来预测情绪和观点,并根据主题的辅助内容和潜在配置文件预测用户的未来行为。

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