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Social Informatics

Overview of attention for book
Social Informatics
Springer, Cham

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 How Well Do Doodle Polls Do?
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    Chapter 2 Bring on Board New Enthusiasts! A Case Study of Impact of Wikipedia Art + Feminism Edit-A-Thon Events on Newcomers
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    Chapter 3 The Social Dynamics of Language Change in Online Networks
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    Chapter 4 On URL Changes and Handovers in Social Media
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    Chapter 5 Comment-Profiler: Detecting Trends and Parasitic Behaviors in Online Comments
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    Chapter 6 On Profiling Bots in Social Media
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    Chapter 7 A Diffusion Model for Maximizing Influence Spread in Large Networks
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    Chapter 8 Lightweight Interactions for Reciprocal Cooperation in a Social Network Game
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    Chapter 9 Continuous Recipe Selection Model Based on Cooking History
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    Chapter 10 Examining Community Policing on Twitter: Precinct Use and Community Response
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    Chapter 11 The Dynamics of Group Risk Perception in the US After Paris Attacks
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    Chapter 12 Determining the Veracity of Rumours on Twitter
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    Chapter 13 PicHunt: Social Media Image Retrieval for Improved Law Enforcement
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    Chapter 14 TwitterNews+: A Framework for Real Time Event Detection from the Twitter Data Stream
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    Chapter 15 Uncovering Topic Dynamics of Social Media and News: The Case of Ferguson
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    Chapter 16 Identifying Partisan Slant in News Articles and Twitter During Political Crises
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    Chapter 17 Predicting Poll Trends Using Twitter and Multivariate Time-Series Classification
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    Chapter 18 Inferring Population Preferences via Mixtures of Spatial Voting Models
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    Chapter 19 Contrasting Public Opinion Dynamics and Emotional Response During Crisis
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    Chapter 20 Social Politics: Agenda Setting and Political Communication on Social Media
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    Chapter 21 Preference-Aware Successive POI Recommendation with Spatial and Temporal Influence
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    Chapter 22 Event Participation Recommendation in Event-Based Social Networks
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    Chapter 23 An Effective Approach to Finding a Context Path in Review Texts Using Pathfinder Scaling
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    Chapter 24 How to Find Accessible Free Wi-Fi at Tourist Spots in Japan
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    Chapter 25 Mobile Communication Signatures of Unemployment
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    Chapter 26 Identifying Stereotypes in the Online Perception of Physical Attractiveness
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    Chapter 27 Analysing RateMyProfessors Evaluations Across Institutions, Disciplines, and Cultures: The Tell-Tale Signs of a Good Professor
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    Chapter 28 Detecting Coping Style from Twitter
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    Chapter 29 User Privacy Concerns with Common Data Used in Recommender Systems
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    Chapter 30 How a User’s Personality Influences Content Engagement in Social Media
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    Chapter 31 Semi-supervised Knowledge Extraction for Detection of Drugs and Their Effects
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    Chapter 32 Using Social Media to Measure Student Wellbeing: A Large-Scale Study of Emotional Response in Academic Discourse
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    Chapter 33 EmojiNet: Building a Machine Readable Sense Inventory for Emoji
Attention for Chapter 16: Identifying Partisan Slant in News Articles and Twitter During Political Crises
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

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4 X users


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30 Mendeley
1 CiteULike
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Chapter title
Identifying Partisan Slant in News Articles and Twitter During Political Crises
Chapter number 16
Book title
Social Informatics
Published in
Lecture notes in computer science, October 2016
DOI 10.1007/978-3-319-47880-7_16
Book ISBNs
978-3-31-947879-1, 978-3-31-947880-7

Dmytro Karamshuk, Tetyana Lokot, Oleksandr Pryymak, Nishanth Sastry

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 3%
Unknown 29 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 20%
Student > Master 5 17%
Researcher 4 13%
Student > Bachelor 2 7%
Student > Doctoral Student 2 7%
Other 2 7%
Unknown 9 30%
Readers by discipline Count As %
Computer Science 6 20%
Social Sciences 6 20%
Mathematics 2 7%
Economics, Econometrics and Finance 2 7%
Arts and Humanities 1 3%
Other 2 7%
Unknown 11 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 21 March 2017.
All research outputs
of 25,193,883 outputs
Outputs from Lecture notes in computer science
of 8,152 outputs
Outputs of similar age
of 322,552 outputs
Outputs of similar age from Lecture notes in computer science
of 417 outputs
Altmetric has tracked 25,193,883 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,152 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one is in the 42nd percentile – i.e., 42% of its peers scored the same or lower than it.
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 322,552 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 417 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.