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Social Computing and Social Media. Applications and Analytics

Overview of attention for book
Cover of 'Social Computing and Social Media. Applications and Analytics'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Strategies for Communicating Reputation Mechanisms in Crowdsourcing-Based Applications
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    Chapter 2 Collaboration Increase Through Monitoring and Evaluation Mechanisms of the Collaborative Learning Process
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    Chapter 3 ADMemento: A Prototype of Activity Reminder and Assessment Tools for Patients with Alzheimer’s Disease
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    Chapter 4 From GreedEx to GreedEx Tab v2.0: Tool for Learning Greedy Algorithms on iPad Following CIAM Mobile Methodology
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    Chapter 5 Memorializing the Deceased Using Virtual Worlds: A Preliminary Study
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    Chapter 6 Social Media and Elderly People: Research Trends
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    Chapter 7 WhatsApp
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    Chapter 8 An Analysis of Online Discussion Platforms for Academic Deliberation Support
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    Chapter 9 Design of Digital Literacy Environments Based-On Interactive Learning Services
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    Chapter 10 Building up a Verified Page on Facebook Using Information Transparency Guidelines
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    Chapter 11 An MDA Approach to Develop Language-Learning Activities
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    Chapter 12 Designing an Electronic Hand Glove for Teaching Vowels to Deaf Children
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    Chapter 13 Chat-Based Application to Support CSCL Activities
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    Chapter 14 Toward a Supporting System of Communication Skill: The Influence of Functional Roles of Participants in Group Discussion
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    Chapter 15 Sentiment Analysis on Arabic Tweets: Challenges to Dissecting the Language
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    Chapter 16 Analyzing User Experience Through Web Opinion Mining
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    Chapter 17 A Review on Corpus Annotation for Arabic Sentiment Analysis
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    Chapter 18 AraSenTi-Lexicon: A Different Approach
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    Chapter 19 Investigating the Relationship Between Trust and Sentiment Agreement in Arab Twitter Users
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    Chapter 20 Investigating the Polarity of User Postings in a Social System
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    Chapter 21 Intent Classification of Social Media Texts with Machine Learning for Customer Service Improvement
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    Chapter 22 Sentiment Analysis for Micro-blogging Platforms in Arabic
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    Chapter 23 Automatic Tweets Classification Under an Intelligent Agents Framework
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    Chapter 24 User Experiences Around Sentiment Analyses, Facilitating Workplace Learning
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    Chapter 25 Visual Exploration of Urban Data: A Study of Riyadh Taxi Data
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    Chapter 26 Understanding Gendered Spaces Using Social Media Data
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    Chapter 27 Visual Exploration Patterns in Information Visualizations: Insights from Eye Tracking
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    Chapter 28 The Rise of Hackathon-Led Innovation in the MENA Region: Visualizing Spatial and Temporal Dynamics of Time-Bounded Events
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    Chapter 29 How Visual Analytics Unlock Insights into Traffic Incidents in Urban Areas
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    Chapter 30 SparQs: Visual Analytics for Sparking Creativity in Social Media Exploration
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    Chapter 31 Social Networks Serendipity for Educational Learning by Surprise from Big and Small Data Analysis
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    Chapter 32 What People Do on Yik Yak: Analyzing Anonymous Microblogging User Behaviors
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    Chapter 33 BLE-Based Children’s Social Behavior Analysis System for Crime Prevention
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    Chapter 34 Unified Structured Framework for mHealth Analytics: Building an Open and Collaborative Community
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    Chapter 35 Discovering Subway Design Opportunities Using Social Network Data: The Image-Need-Design Opportunity Model
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
1 news outlet
twitter
8 tweeters

Readers on

mendeley
24 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Social Computing and Social Media. Applications and Analytics
Published by
Lecture notes in computer science, January 2017
DOI 10.1007/978-3-319-58562-8
ISBNs
978-3-31-958561-1, 978-3-31-958562-8
Editors

Gabriele Meiselwitz

Twitter Demographics

The data shown below were collected from the profiles of 8 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Postgraduate 3 13%
Student > Ph. D. Student 3 13%
Student > Master 2 8%
Professor > Associate Professor 2 8%
Student > Doctoral Student 1 4%
Other 1 4%
Unknown 12 50%
Readers by discipline Count As %
Computer Science 7 29%
Social Sciences 2 8%
Economics, Econometrics and Finance 1 4%
Arts and Humanities 1 4%
Engineering 1 4%
Other 0 0%
Unknown 12 50%

Attention Score in Context

This research output has an Altmetric Attention Score of 19. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 December 2017.
All research outputs
#758,085
of 12,820,093 outputs
Outputs from Lecture notes in computer science
#197
of 7,331 outputs
Outputs of similar age
#27,913
of 261,537 outputs
Outputs of similar age from Lecture notes in computer science
#5
of 129 outputs
Altmetric has tracked 12,820,093 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,331 research outputs from this source. They receive a mean Attention Score of 4.4. This one has done particularly well, scoring higher than 97% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 261,537 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 129 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.