Network Media Public Opinion and Social Governance Supported by the Internet-of-Things Big Data
نویسندگان
چکیده
The purpose is to make for the traditional Network Public Opinion (NPO) analysis methods’ inadequacy in era of big data and provide a sufficient decision-making basis managers. Based on Internet Things (IoT) data, this work applies Natural Language Processing (NLP) NPO analysis. Additionally, it takes content Microblog text format as main collection target, constructs tool, establishes Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Deep Pyramid Convolutional Neural (DPCNN) based Tensorflow other deep learning models. It also improved combination with characteristics model, new model proposed. Finally, performance various models compared analyzed through experiments, path proposed government use improve ability govern help social governance. results show that LSTM can correctly classify extracted text’s emotion by much 80.00%. improves classification accuracy nearly two percentage points under ideal condition. Thus, adding residual connection attention mechanism, extract emotional features better discrimination ability. public opinion online media without effective control will have great security risks governance IoT. method analyzing accurate text.
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ژورنال
عنوان ژورنال: Security and Communication Networks
سال: 2022
ISSN: ['1939-0122', '1939-0114']
DOI: https://doi.org/10.1155/2022/2459815