Supermajority sentiment detection with external influence in large social networks
Supermajority sentiment detection with external influence in large social networks
复制标题
大型社交网络中受外部影响的绝大多数情绪检测
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
R. Negi
中科院分区：
文献类型：
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作者：
Tian Tong;R. Negi
在一个大型的社会网络，其成员怀有二元情绪对一个问题，我们调查的渐近精度的情绪检测。我们通过一个伊辛马尔可夫随机场模型来模拟用户情绪，并允许用户情绪受到外部影响的偏见。我们考虑了一个一般的绝大多数情感检测问题，并表明检测精度受到网络结构，参数以及外部影响水平的影响。
In a large social network whose members harbor binary sentiments towards an issue, we investigate the asymptotic accuracy of sentiment detection. We model the user sentiments by an Ising Markov random field model and allow the user sentiments to be biased by an external influence. We consider a general supermajority sentiment detection problem and show that the detection accuracy is affected by the network structure, its parameters, as well as the external influence level.