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Mendeley readers
Attention Score in Context
| Chapter title |
Bullying in Virtual Learning Communities
|
|---|---|
| Chapter number | 18 |
| Book title |
GeNeDis 2016
|
| Published in |
Advances in experimental medicine and biology, October 2017
|
| DOI | 10.1007/978-3-319-57348-9_18 |
| Pubmed ID | |
| Book ISBNs |
978-3-31-957347-2, 978-3-31-957348-9
|
| Authors |
Nikiforos, Stefanos, Tzanavaris, Spyros, Kermanidis, Katia Lida, Stefanos Nikiforos, Spyros Tzanavaris, Katia Lida Kermanidis |
| Abstract |
Bullying through the internet has been investigated and analyzed mainly in the field of social media. In this paper, it is attempted to analyze bullying in the Virtual Learning Communities using Natural Language Processing (NLP) techniques, mainly in the context of sociocultural learning theories. Therefore four case studies took place. We aim to apply NLP techniques to speech analysis on communication data of online communities. Emphasis is given on qualitative data, taking into account the subjectivity of the collaborative activity. Finally, this is the first time such type of analysis is attempted on Greek data. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 14 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 4 | 29% |
| Student > Ph. D. Student | 3 | 21% |
| Unspecified | 2 | 14% |
| Researcher | 2 | 14% |
| Librarian | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 1 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 5 | 36% |
| Unspecified | 2 | 14% |
| Social Sciences | 2 | 14% |
| Medicine and Dentistry | 2 | 14% |
| Unknown | 3 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 04 May 2019.
All research outputs
#17,917,778
of 23,005,189 outputs
Outputs from Advances in experimental medicine and biology
#3,112
of 4,961 outputs
Outputs of similar age
#231,058
of 323,064 outputs
Outputs of similar age from Advances in experimental medicine and biology
#24
of 35 outputs
Altmetric has tracked 23,005,189 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,961 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one is in the 32nd percentile – i.e., 32% 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 323,064 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.