Mastering social media mining with R :: extract valuable data from social media sites and make better business decisions using R /
Chapter 3: Find Friends on Facebook ; Creating an app on the Facebook platform; Rfacebook package installation and authentication; Installation; A closer look at how the package works; A basic analysis of your network; Network analysis and visualization; Social network analysis; Degree; Betweenness;...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham, UK :
Packt Publishing,
2015.
|
| Schriftenreihe: | Community experience distilled.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | Chapter 3: Find Friends on Facebook ; Creating an app on the Facebook platform; Rfacebook package installation and authentication; Installation; A closer look at how the package works; A basic analysis of your network; Network analysis and visualization; Social network analysis; Degree; Betweenness; Closeness; Cluster; Communities; Getting Facebook page data; Trending topics; Trend analysis; Influencers; Based on a single post; Based on multiple posts; Measuring CTR performance for a page; Spam detection; Implementing a spam detection algorithm |
| Beschreibung: | Includes index. |
| Beschreibung: | 1 online resource (1 volume) : illustrations |
| ISBN: | 9781784399672 1784399671 |
Internformat
MARC
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| 100 | 1 | |a Ravindran, Sharan Kumar, |e author. |0 http://id.loc.gov/authorities/names/no2016023694 | |
| 245 | 1 | 0 | |a Mastering social media mining with R : |b extract valuable data from social media sites and make better business decisions using R / |c Sharan Kumar Ravindran, Vikram Garg. |
| 246 | 3 | 0 | |a Extract valuable data from social media sites and make better business decisions using R |
| 264 | 1 | |a Birmingham, UK : |b Packt Publishing, |c 2015. | |
| 300 | |a 1 online resource (1 volume) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Community experience distilled | |
| 588 | 0 | |a Online resource; title from cover page (Safari, viewed October 12, 2015). | |
| 500 | |a Includes index. | ||
| 505 | 0 | |a Cover ; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Fundamentals of Mining; Social media and its importance; Various social media platforms; Social media mining; Challenges for social media mining; Social media mining techniques; Graph mining; Text mining; The generic process of social media mining; Getting authentication from the social website -- OAuth 2.0; Differences between OAuth and OAuth 2.0; Data visualization R packages; The simple word cloud; Sentiment analysis Wordcloud; Preprocessing and cleaning in R | |
| 505 | 8 | |a Data modeling -- the application of mining algorithmsOpinion mining (sentiment analysis); Steps for sentiment analysis; Community detection via clustering ; Result visualization; An example of social media mining; Summary; Chapter 2: Mining Opinions, Exploring Trends, and More with Twitter ; Twitter and its importance; Understanding Twitter's APIs; Twitter vocabulary; Creating a Twitter API connection; Creating a new app; Finding trending topics; Searching tweets; Twitter sentiment analysis; Collecting tweets as a corpus; Cleaning the corpus; Estimating sentiment (A); Estimating sentiment (B) | |
| 505 | 8 | |a The order of stories on a user's home pageRecommendations to friends; Reading the output; Other business cases; Summary; Chapter 4: Finding Popular Photos on Instagram ; Creating an app on the Instagram platform; Installation and authentication of the instaR package; Accessing data from R; Searching public media for a specific hashtag; Searching public media from a specific location; Extracting public media of a user; Extracting user profile; Getting followers; Who does the user follow?; Getting comments; Number of times hashtag is used; Building a dataset; User profile; User media | |
| 505 | 8 | |a Travel-related mediaWho do they follow?; Popular personalities; Who has the most followers?; Who follows more people?; Who shared most media?; Overall top users; Most viral media; Finding the most popular destination; Locations; Locations with most likes; Locations most talked about; What are people saying about these locations?; Most repeating locations; Clustering the pictures; Recommendations to the users; How to do it; Top three recommendations; Improvements to the recommendation system; Business case; Reference; Summary; Chapter 5: Let's Build Software with GitHub | |
| 520 | |a Chapter 3: Find Friends on Facebook ; Creating an app on the Facebook platform; Rfacebook package installation and authentication; Installation; A closer look at how the package works; A basic analysis of your network; Network analysis and visualization; Social network analysis; Degree; Betweenness; Closeness; Cluster; Communities; Getting Facebook page data; Trending topics; Trend analysis; Influencers; Based on a single post; Based on multiple posts; Measuring CTR performance for a page; Spam detection; Implementing a spam detection algorithm | ||
| 546 | |a English. | ||
| 650 | 0 | |a Data mining. |0 http://id.loc.gov/authorities/subjects/sh97002073 | |
| 650 | 0 | |a R (Computer program language) |0 http://id.loc.gov/authorities/subjects/sh2002004407 | |
| 650 | 0 | |a Social media. |0 http://id.loc.gov/authorities/subjects/sh2006007023 | |
| 650 | 6 | |a Exploration de données (Informatique) | |
| 650 | 6 | |a R (Langage de programmation) | |
| 650 | 6 | |a Médias sociaux. | |
| 650 | 7 | |a social media. |2 aat | |
| 650 | 7 | |a COMPUTERS |x General. |2 bisacsh | |
| 650 | 7 | |a Data mining |2 fast | |
| 650 | 7 | |a R (Computer program language) |2 fast | |
| 650 | 7 | |a Social media |2 fast | |
| 700 | 1 | |a Garg, Vikram, |e author. |0 http://id.loc.gov/authorities/names/no2016023677 | |
| 758 | |i has work: |a Mastering social media mining with R (Text) |1 https://id.oclc.org/worldcat/entity/E39PCFBcPVFrJ8hq7fXPjGGQ4m |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
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| author | Ravindran, Sharan Kumar Garg, Vikram |
| author_GND | http://id.loc.gov/authorities/names/no2016023694 http://id.loc.gov/authorities/names/no2016023677 |
| author_facet | Ravindran, Sharan Kumar Garg, Vikram |
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| contents | Cover ; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Fundamentals of Mining; Social media and its importance; Various social media platforms; Social media mining; Challenges for social media mining; Social media mining techniques; Graph mining; Text mining; The generic process of social media mining; Getting authentication from the social website -- OAuth 2.0; Differences between OAuth and OAuth 2.0; Data visualization R packages; The simple word cloud; Sentiment analysis Wordcloud; Preprocessing and cleaning in R Data modeling -- the application of mining algorithmsOpinion mining (sentiment analysis); Steps for sentiment analysis; Community detection via clustering ; Result visualization; An example of social media mining; Summary; Chapter 2: Mining Opinions, Exploring Trends, and More with Twitter ; Twitter and its importance; Understanding Twitter's APIs; Twitter vocabulary; Creating a Twitter API connection; Creating a new app; Finding trending topics; Searching tweets; Twitter sentiment analysis; Collecting tweets as a corpus; Cleaning the corpus; Estimating sentiment (A); Estimating sentiment (B) The order of stories on a user's home pageRecommendations to friends; Reading the output; Other business cases; Summary; Chapter 4: Finding Popular Photos on Instagram ; Creating an app on the Instagram platform; Installation and authentication of the instaR package; Accessing data from R; Searching public media for a specific hashtag; Searching public media from a specific location; Extracting public media of a user; Extracting user profile; Getting followers; Who does the user follow?; Getting comments; Number of times hashtag is used; Building a dataset; User profile; User media Travel-related mediaWho do they follow?; Popular personalities; Who has the most followers?; Who follows more people?; Who shared most media?; Overall top users; Most viral media; Finding the most popular destination; Locations; Locations with most likes; Locations most talked about; What are people saying about these locations?; Most repeating locations; Clustering the pictures; Recommendations to the users; How to do it; Top three recommendations; Improvements to the recommendation system; Business case; Reference; Summary; Chapter 5: Let's Build Software with GitHub |
| ctrlnum | (OCoLC)924210506 |
| dewey-full | 006.3/12 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3/12 |
| dewey-search | 006.3/12 |
| dewey-sort | 16.3 212 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Electronic eBook |
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| id | ZDB-4-EBA-ocn924210506 |
| illustrated | Illustrated |
| indexdate | 2024-11-27T13:26:50Z |
| institution | BVB |
| isbn | 9781784399672 1784399671 |
| language | English |
| oclc_num | 924210506 |
| open_access_boolean | |
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| publisher | Packt Publishing, |
| record_format | marc |
| series | Community experience distilled. |
| series2 | Community experience distilled |
| spelling | Ravindran, Sharan Kumar, author. http://id.loc.gov/authorities/names/no2016023694 Mastering social media mining with R : extract valuable data from social media sites and make better business decisions using R / Sharan Kumar Ravindran, Vikram Garg. Extract valuable data from social media sites and make better business decisions using R Birmingham, UK : Packt Publishing, 2015. 1 online resource (1 volume) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Community experience distilled Online resource; title from cover page (Safari, viewed October 12, 2015). Includes index. Cover ; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Fundamentals of Mining; Social media and its importance; Various social media platforms; Social media mining; Challenges for social media mining; Social media mining techniques; Graph mining; Text mining; The generic process of social media mining; Getting authentication from the social website -- OAuth 2.0; Differences between OAuth and OAuth 2.0; Data visualization R packages; The simple word cloud; Sentiment analysis Wordcloud; Preprocessing and cleaning in R Data modeling -- the application of mining algorithmsOpinion mining (sentiment analysis); Steps for sentiment analysis; Community detection via clustering ; Result visualization; An example of social media mining; Summary; Chapter 2: Mining Opinions, Exploring Trends, and More with Twitter ; Twitter and its importance; Understanding Twitter's APIs; Twitter vocabulary; Creating a Twitter API connection; Creating a new app; Finding trending topics; Searching tweets; Twitter sentiment analysis; Collecting tweets as a corpus; Cleaning the corpus; Estimating sentiment (A); Estimating sentiment (B) The order of stories on a user's home pageRecommendations to friends; Reading the output; Other business cases; Summary; Chapter 4: Finding Popular Photos on Instagram ; Creating an app on the Instagram platform; Installation and authentication of the instaR package; Accessing data from R; Searching public media for a specific hashtag; Searching public media from a specific location; Extracting public media of a user; Extracting user profile; Getting followers; Who does the user follow?; Getting comments; Number of times hashtag is used; Building a dataset; User profile; User media Travel-related mediaWho do they follow?; Popular personalities; Who has the most followers?; Who follows more people?; Who shared most media?; Overall top users; Most viral media; Finding the most popular destination; Locations; Locations with most likes; Locations most talked about; What are people saying about these locations?; Most repeating locations; Clustering the pictures; Recommendations to the users; How to do it; Top three recommendations; Improvements to the recommendation system; Business case; Reference; Summary; Chapter 5: Let's Build Software with GitHub Chapter 3: Find Friends on Facebook ; Creating an app on the Facebook platform; Rfacebook package installation and authentication; Installation; A closer look at how the package works; A basic analysis of your network; Network analysis and visualization; Social network analysis; Degree; Betweenness; Closeness; Cluster; Communities; Getting Facebook page data; Trending topics; Trend analysis; Influencers; Based on a single post; Based on multiple posts; Measuring CTR performance for a page; Spam detection; Implementing a spam detection algorithm English. Data mining. http://id.loc.gov/authorities/subjects/sh97002073 R (Computer program language) http://id.loc.gov/authorities/subjects/sh2002004407 Social media. http://id.loc.gov/authorities/subjects/sh2006007023 Exploration de données (Informatique) R (Langage de programmation) Médias sociaux. social media. aat COMPUTERS General. bisacsh Data mining fast R (Computer program language) fast Social media fast Garg, Vikram, author. http://id.loc.gov/authorities/names/no2016023677 has work: Mastering social media mining with R (Text) https://id.oclc.org/worldcat/entity/E39PCFBcPVFrJ8hq7fXPjGGQ4m https://id.oclc.org/worldcat/ontology/hasWork 1-78439-631-1 Community experience distilled. http://id.loc.gov/authorities/names/no2011030603 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1071006 Volltext |
| spellingShingle | Ravindran, Sharan Kumar Garg, Vikram Mastering social media mining with R : extract valuable data from social media sites and make better business decisions using R / Community experience distilled. Cover ; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Fundamentals of Mining; Social media and its importance; Various social media platforms; Social media mining; Challenges for social media mining; Social media mining techniques; Graph mining; Text mining; The generic process of social media mining; Getting authentication from the social website -- OAuth 2.0; Differences between OAuth and OAuth 2.0; Data visualization R packages; The simple word cloud; Sentiment analysis Wordcloud; Preprocessing and cleaning in R Data modeling -- the application of mining algorithmsOpinion mining (sentiment analysis); Steps for sentiment analysis; Community detection via clustering ; Result visualization; An example of social media mining; Summary; Chapter 2: Mining Opinions, Exploring Trends, and More with Twitter ; Twitter and its importance; Understanding Twitter's APIs; Twitter vocabulary; Creating a Twitter API connection; Creating a new app; Finding trending topics; Searching tweets; Twitter sentiment analysis; Collecting tweets as a corpus; Cleaning the corpus; Estimating sentiment (A); Estimating sentiment (B) The order of stories on a user's home pageRecommendations to friends; Reading the output; Other business cases; Summary; Chapter 4: Finding Popular Photos on Instagram ; Creating an app on the Instagram platform; Installation and authentication of the instaR package; Accessing data from R; Searching public media for a specific hashtag; Searching public media from a specific location; Extracting public media of a user; Extracting user profile; Getting followers; Who does the user follow?; Getting comments; Number of times hashtag is used; Building a dataset; User profile; User media Travel-related mediaWho do they follow?; Popular personalities; Who has the most followers?; Who follows more people?; Who shared most media?; Overall top users; Most viral media; Finding the most popular destination; Locations; Locations with most likes; Locations most talked about; What are people saying about these locations?; Most repeating locations; Clustering the pictures; Recommendations to the users; How to do it; Top three recommendations; Improvements to the recommendation system; Business case; Reference; Summary; Chapter 5: Let's Build Software with GitHub Data mining. http://id.loc.gov/authorities/subjects/sh97002073 R (Computer program language) http://id.loc.gov/authorities/subjects/sh2002004407 Social media. http://id.loc.gov/authorities/subjects/sh2006007023 Exploration de données (Informatique) R (Langage de programmation) Médias sociaux. social media. aat COMPUTERS General. bisacsh Data mining fast R (Computer program language) fast Social media fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh97002073 http://id.loc.gov/authorities/subjects/sh2002004407 http://id.loc.gov/authorities/subjects/sh2006007023 |
| title | Mastering social media mining with R : extract valuable data from social media sites and make better business decisions using R / |
| title_alt | Extract valuable data from social media sites and make better business decisions using R |
| title_auth | Mastering social media mining with R : extract valuable data from social media sites and make better business decisions using R / |
| title_exact_search | Mastering social media mining with R : extract valuable data from social media sites and make better business decisions using R / |
| title_full | Mastering social media mining with R : extract valuable data from social media sites and make better business decisions using R / Sharan Kumar Ravindran, Vikram Garg. |
| title_fullStr | Mastering social media mining with R : extract valuable data from social media sites and make better business decisions using R / Sharan Kumar Ravindran, Vikram Garg. |
| title_full_unstemmed | Mastering social media mining with R : extract valuable data from social media sites and make better business decisions using R / Sharan Kumar Ravindran, Vikram Garg. |
| title_short | Mastering social media mining with R : |
| title_sort | mastering social media mining with r extract valuable data from social media sites and make better business decisions using r |
| title_sub | extract valuable data from social media sites and make better business decisions using R / |
| topic | Data mining. http://id.loc.gov/authorities/subjects/sh97002073 R (Computer program language) http://id.loc.gov/authorities/subjects/sh2002004407 Social media. http://id.loc.gov/authorities/subjects/sh2006007023 Exploration de données (Informatique) R (Langage de programmation) Médias sociaux. social media. aat COMPUTERS General. bisacsh Data mining fast R (Computer program language) fast Social media fast |
| topic_facet | Data mining. R (Computer program language) Social media. Exploration de données (Informatique) R (Langage de programmation) Médias sociaux. social media. COMPUTERS General. Data mining Social media |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1071006 |
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