| 000 | 03755nam a22006135i 4500 | ||
|---|---|---|---|
| 001 | 978-3-031-33617-1 | ||
| 003 | DE-He213 | ||
| 005 | 20240423125527.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 230705s2023 sz | s |||| 0|eng d | ||
| 020 |
_a9783031336171 _9978-3-031-33617-1 |
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| 024 | 7 |
_a10.1007/978-3-031-33617-1 _2doi |
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| 050 | 4 | _aQA76.9.Q36 | |
| 072 | 7 |
_aUN _2bicssc |
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_aCOM021000 _2bisacsh |
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_aUN _2thema |
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_a001.422 _223 |
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_a005.7 _223 |
| 100 | 1 |
_aMatwin, Stan. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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| 245 | 1 | 0 |
_aGenerative Methods for Social Media Analysis _h[electronic resource] / _cby Stan Matwin, Aristides Milios, Paweł Prałat, Amilcar Soares, François Théberge. |
| 250 | _a1st ed. 2023. | ||
| 264 | 1 |
_aCham : _bSpringer Nature Switzerland : _bImprint: Springer, _c2023. |
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| 300 |
_aVII, 90 p. 5 illus., 4 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 |
_aSpringerBriefs in Computer Science, _x2191-5776 |
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| 505 | 0 | _a1. Introduction -- 2. Ontologies and Data Models for Cross-platform Social Media Data -- 3. Methods for Text Generation in NLP -- 4. Topic and Sentiment Modelling for Social Media -- 5. Mining and Modelling Complex Networks -- 6. Conclusions. | |
| 520 | _aThis book provides a broad overview of the state of the art of the research in generative methods for the analysis of social media data. It especially includes two important aspects that currently gain importance in mining and modelling social media: dynamics and networks. The book is divided into five chapters and provides an extensive bibliography consisting of more than 250 papers. After a quick introduction and survey of the book in the first chapter, chapter 2 is devoted to the discussion of data models and ontologies for social network analysis. Next, chapter 3 deals with text generation and generative text models and the dangers they pose to social media and society at large. Chapter 4 then focuses on topic modelling and sentiment analysis in the context of social networks. Finally, Chapter 5 presents graph theory tools and approaches to mine and model social networks. Throughout the book, open problems, highlighting potential future directions, are clearly identified. The book aims at researchers and graduate students in social media analysis, information retrieval, and machine learning applications. | ||
| 650 | 0 | _aQuantitative research. | |
| 650 | 0 | _aArtificial intelligence. | |
| 650 | 0 | _aNatural language processing (Computer science). | |
| 650 | 0 | _aSocial media. | |
| 650 | 1 | 4 | _aData Analysis and Big Data. |
| 650 | 2 | 4 | _aArtificial Intelligence. |
| 650 | 2 | 4 | _aNatural Language Processing (NLP). |
| 650 | 2 | 4 | _aSocial Media. |
| 700 | 1 |
_aMilios, Aristides. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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| 700 | 1 |
_aPrałat, Paweł. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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| 700 | 1 |
_aSoares, Amilcar. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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| 700 | 1 |
_aThéberge, François. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783031336164 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783031336188 |
| 830 | 0 |
_aSpringerBriefs in Computer Science, _x2191-5776 |
|
| 856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-33617-1 |
| 912 | _aZDB-2-SCS | ||
| 912 | _aZDB-2-SXCS | ||
| 942 | _cSPRINGER | ||
| 999 |
_c178912 _d178912 |
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