000 | 03847nam a22006255i 4500 | ||
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001 | 978-3-031-10869-3 | ||
003 | DE-He213 | ||
005 | 20240423125034.0 | ||
007 | cr nn 008mamaa | ||
008 | 220918s2022 sz | s |||| 0|eng d | ||
020 |
_a9783031108693 _9978-3-031-10869-3 |
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024 | 7 |
_a10.1007/978-3-031-10869-3 _2doi |
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072 | 7 |
_aUN _2bicssc |
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_aCOM018000 _2bisacsh |
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_a620.00285 _223 |
245 | 1 | 0 |
_aDeep Learning for Social Media Data Analytics _h[electronic resource] / _cedited by Tzung-Pei Hong, Leticia Serrano-Estrada, Akrati Saxena, Anupam Biswas. |
250 | _a1st ed. 2022. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2022. |
|
300 |
_aX, 299 p. 86 illus., 65 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aStudies in Big Data, _x2197-6511 ; _v113 |
|
505 | 0 | _aNode Classification using Deep Learning in Social Networks -- NN-LP-CF: Neural Network based Link Prediction on Social Networks using Centrality-based Features -- Deep Learning for Code-Mixed Text Mining in Social Media: A Brief Review -- Convolutional and Recurrent Neural Networks for Opinion Mining on Drug Reviews -- Text-based Sentiment Analysis using Deep Learning Techniques -- Social Sentiment Analysis Using Features based Intelligent Learning Techniques. | |
520 | _aThis edited book covers ongoing research in both theory and practical applications of using deep learning for social media data. Social networking platforms are overwhelmed by different contents, and their huge amounts of data have enormous potential to influence business, politics, security, planning and other social aspects. Recently, deep learning techniques have had many successful applications in the AI field. The research presented in this book emerges from the conviction that there is still much progress to be made toward exploiting deep learning in the context of social media data analytics. It includes fifteen chapters, organized into four sections that report on original research in network structure analysis, social media text analysis, user behaviour analysis and social media security analysis. This work could serve as a good reference for researchers, as well as a compilation of innovative ideas and solutions for practitioners interested in applying deep learning techniques to social media data analytics. . | ||
650 | 0 |
_aEngineering _xData processing. |
|
650 | 0 | _aCooperating objects (Computer systems). | |
650 | 0 | _aComputational intelligence. | |
650 | 0 | _aBig data. | |
650 | 0 | _aSocial media. | |
650 | 1 | 4 | _aData Engineering. |
650 | 2 | 4 | _aCyber-Physical Systems. |
650 | 2 | 4 | _aComputational Intelligence. |
650 | 2 | 4 | _aBig Data. |
650 | 2 | 4 | _aSocial Media. |
700 | 1 |
_aHong, Tzung-Pei. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aSerrano-Estrada, Leticia. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aSaxena, Akrati. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aBiswas, Anupam. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783031108686 |
776 | 0 | 8 |
_iPrinted edition: _z9783031108709 |
776 | 0 | 8 |
_iPrinted edition: _z9783031108716 |
830 | 0 |
_aStudies in Big Data, _x2197-6511 ; _v113 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-10869-3 |
912 | _aZDB-2-SCS | ||
912 | _aZDB-2-SXCS | ||
942 | _cSPRINGER | ||
999 |
_c173525 _d173525 |