語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Early Detection of Mental Health Disorders by Social Media Monitoring = The First Five Years of the eRisk Project /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Early Detection of Mental Health Disorders by Social Media Monitoring/ edited by Fabio Crestani, David E. Losada, Javier Parapar.
其他題名:
The First Five Years of the eRisk Project /
其他作者:
Parapar, Javier.
面頁冊數:
XII, 328 p. 70 illus., 50 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Social Media. -
電子資源:
https://doi.org/10.1007/978-3-031-04431-1
ISBN:
9783031044311
Early Detection of Mental Health Disorders by Social Media Monitoring = The First Five Years of the eRisk Project /
Early Detection of Mental Health Disorders by Social Media Monitoring
The First Five Years of the eRisk Project /[electronic resource] :edited by Fabio Crestani, David E. Losada, Javier Parapar. - 1st ed. 2022. - XII, 328 p. 70 illus., 50 illus. in color.online resource. - Studies in Computational Intelligence,10181860-9503 ;. - Studies in Computational Intelligence,564.
Early Risk Prediction of Mental Health Disorders -- The Challenge of Early Risk Prediction on the Internet -- A Survey of the First Five Years of eRisk: Findings and Conclusions -- From Bag-of-Words to Transformers: A Deep Dive into the Participation in the eRisk Early Risk Detection of Depression Tasks with Classical and new Approaches.
eRisk stands for Early Risk Prediction on the Internet. It is concerned with the exploration of techniques for the early detection of mental health disorders which manifest in the way people write and communicate on the internet, in particular in user generated content (e.g. Facebook, Twitter, or other social media). Early detection technologies can be employed in several different areas but particularly in those related to health and safety. For instance, early alerts could be sent when the writing of a teenager starts showing increasing signs of depression, or when a social media user starts showing suicidal inclinations, or again when a potential offender starts publishing antisocial threats on a blog, forum or social network. eRisk has been the pioneer of a new interdisciplinary area of research that is potentially applicable to a wide variety of situations, problems and personal profiles. This book presents the best results of the first five years of the eRisk project which started in 2017 and developed into one of the most successful track of CLEF, the Conference and Lab of the Evaluation Forum.
ISBN: 9783031044311
Standard No.: 10.1007/978-3-031-04431-1doiSubjects--Topical Terms:
1106917
Social Media.
LC Class. No.: Q342
Dewey Class. No.: 006.3
Early Detection of Mental Health Disorders by Social Media Monitoring = The First Five Years of the eRisk Project /
LDR
:03010nam a22004095i 4500
001
1083137
003
DE-He213
005
20220914222558.0
007
cr nn 008mamaa
008
221228s2022 sz | s |||| 0|eng d
020
$a
9783031044311
$9
978-3-031-04431-1
024
7
$a
10.1007/978-3-031-04431-1
$2
doi
035
$a
978-3-031-04431-1
050
4
$a
Q342
072
7
$a
UYQ
$2
bicssc
072
7
$a
TEC009000
$2
bisacsh
072
7
$a
UYQ
$2
thema
082
0 4
$a
006.3
$2
23
245
1 0
$a
Early Detection of Mental Health Disorders by Social Media Monitoring
$h
[electronic resource] :
$b
The First Five Years of the eRisk Project /
$c
edited by Fabio Crestani, David E. Losada, Javier Parapar.
250
$a
1st ed. 2022.
264
1
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2022.
300
$a
XII, 328 p. 70 illus., 50 illus. in color.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
490
1
$a
Studies in Computational Intelligence,
$x
1860-9503 ;
$v
1018
505
0
$a
Early Risk Prediction of Mental Health Disorders -- The Challenge of Early Risk Prediction on the Internet -- A Survey of the First Five Years of eRisk: Findings and Conclusions -- From Bag-of-Words to Transformers: A Deep Dive into the Participation in the eRisk Early Risk Detection of Depression Tasks with Classical and new Approaches.
520
$a
eRisk stands for Early Risk Prediction on the Internet. It is concerned with the exploration of techniques for the early detection of mental health disorders which manifest in the way people write and communicate on the internet, in particular in user generated content (e.g. Facebook, Twitter, or other social media). Early detection technologies can be employed in several different areas but particularly in those related to health and safety. For instance, early alerts could be sent when the writing of a teenager starts showing increasing signs of depression, or when a social media user starts showing suicidal inclinations, or again when a potential offender starts publishing antisocial threats on a blog, forum or social network. eRisk has been the pioneer of a new interdisciplinary area of research that is potentially applicable to a wide variety of situations, problems and personal profiles. This book presents the best results of the first five years of the eRisk project which started in 2017 and developed into one of the most successful track of CLEF, the Conference and Lab of the Evaluation Forum.
650
2 4
$a
Social Media.
$3
1106917
650
2 4
$a
Data Engineering.
$3
1226308
650
1 4
$a
Computational Intelligence.
$3
768837
650
0
$a
Social media.
$3
780265
650
0
$a
Engineering—Data processing.
$3
1297966
650
0
$a
Computational intelligence.
$3
568984
700
1
$a
Parapar, Javier.
$e
editor.
$1
https://orcid.org/0000-0002-5997-8252
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
1389046
700
1
$a
Losada, David E.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
674813
700
1
$a
Crestani, Fabio.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
675082
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9783031044304
776
0 8
$i
Printed edition:
$z
9783031044328
776
0 8
$i
Printed edition:
$z
9783031044335
830
0
$a
Studies in Computational Intelligence,
$x
1860-949X ;
$v
564
$3
1253640
856
4 0
$u
https://doi.org/10.1007/978-3-031-04431-1
912
$a
ZDB-2-INR
912
$a
ZDB-2-SXIT
950
$a
Intelligent Technologies and Robotics (SpringerNature-42732)
950
$a
Intelligent Technologies and Robotics (R0) (SpringerNature-43728)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入