Hello All,
Special issue of the *Social Network Analysis and Mining (SNAM)* journal:
*Datasets, Language Resources and Algorithmic Approaches on Online Wellbeing*
*and Social Order in Asian Languages*
https://link.springer.com/journal/13278/updates/26741080
*** Deadline for submission: July 2024 ***
*** Guest Editors ***
Vivek Kumar Singh, Banaras Hindu University, Varanasi, India
David Pinto, Benemerita Universidad Autonoma de Puebla, Mexico
Dr Sriparna Saha, Indian Institute of Technology, Patna, India
Dr. Vedika Gupta, OP Jindal Global University, Haryana, India.
Dr. Rajesh Sharma, University of Tartu, Estonia.
*** Context ***
The phenomenal growth of social media platforms has resulted in their becoming ubiquitous in the sense that now almost everyone on the planet is using or is being affected by content on social media platforms. Social media platforms have become so influential that they are not only affecting individual thoughts and behaviours but also guiding collective behaviours of groups and societies. There are now innumerable instances of hate speech, abusive content, cyberbullying, misogyny, fake news and disinformation etc. on social media platforms. Such content can severely impact our emotions, mental health, and well-being. The spread of hate speech, misinformation, fundamentalist propaganda, religious hate campaigns etc. on social media platforms can be furthermore dangerous as it could disturb the social order and harmony. The hateful and targeted campaigns can affect social structures and institutions, values, and norms. Therefore, it is extremely important that such content is identified and appropriately dealt with. However, due the huge volume and speed of creation of such content, it can only be done by using sophisticated computational methods that can automatically detect and identify harmful content. Taking into account the fact that the social media is accessible in large number of languages across the world, the task becomes more challenging.
Availability of enough and suitable data and resources is a fundamental requirement towards this endeavour. Asia, being the largest continent, embraces diverse cultures, ethnicities and languages. There are around 2300 languages spoken in Asia. Though there has been substantial research on the above mentioned aspects in the English language, research in Asian languages is still in its infancy. The limited or availability of no datasets and resources in these languages is a primary reason for this. This special issue aims to bring together contributions that advance the research in the area of computational methods for automatic detection and identification of harmful content on the social media platforms, such as those reporting:
· Algorithmic approaches
· Computational resources
· Datasets
· Dictionaries and Lexicons
· Software Resources
Contributions that report novel methods and techniques, datasets and application of various state of the art methods for different tasks in the social media text analytics, including those in low resource languages are also welcome. Though the main focus area of the special issue is on the analysis of the textual content, studies and resources that report multimodal data (with text being the major part) will also be considered.
***Topics of Interest***
The special issue invites original, unpublished contributions on datasets (elicitation, processing, annotation) and resources (corpora, lexica, database, ontologies, computational approaches, and methodologies) on the following non-exhaustive list of indicative topics:
· Aggression and Abusive Content detection
· Cognitive Analytics of Social Media Services
· Collective Idea Generation and Opinion Dynamics
· Depression Intensity Estimation
· Detection of Hate Speech, Profanity, Hostility, Cyberbullying
· Disinformation, Misinformation, Fake News and Rumours
· Emotion analysis, Emotional conversation generation
· Fraud detection in online social network
· Making online environments safer
· Personality trait assessment
· Polarization in online discussions
· Protecting Children from abusive content
· Racial and targeted abuse detection
· Religious abuse and bias detection
· Sentiment Analysis
· Sexism and Misogynistic attitude detection
· Social Alignment Contagion in Online Social Networks
· Social biases in online texts
· Social Perception and Social Influence in social media
· Suicide Ideation detection in the Online Environment
· Violent Incident detection
*** Important dates ***
• Submission deadline: July 2024
• Notification to the authors after the first review: December 2024
• Notification to the authors after the second review: March 2025
• Publication: December 2024
*** Submission Guidelines ***
Articles reporting original and unpublished research results pertaining to the above topics are solicited. Submitted articles will follow an academic review process. Manuscripts must be prepared according to the instructions for authors available at the journal webpage and submitted through the publisher's online submission system, available here https://idp-personal-authenticator.springernature.com/gateway?response_type=code&redirect_uri=https%3A%2F%2Fidp.springernature.com%2Fauthed%2Fpersonal&state=eyJjdHkiOiJKV1QiLCJlbmMiOiJBMTI4R0NNIiwiYWxnIjoiZGlyIn0..XPRqvWidSoxCCsVt.bmBjuaOsEYjaTYq8lzDDQjIc_aaA13FAtUG1CzBeuX-ZYv39XSaaP6n3zbrDbvoL4kym33NYH_aHFl4gZTKxnG8qS6C7Zw2q09q-_FQtX1-wPfmqHFvIXZ7tD4gUjUhi6iIjhvwvg_Br8dlQ8JlabC4RZl_mA4_i6LmM856M3Eeho3gDm7ipOCv4KPJG72aC2LR3mp11c5JpIa9MXI3jjzpclhedPfTHQprNUprmI79Fgo7AFaV5EKIwUSODkhmkCazZzk0Kqvw88oP4VLEpUS0M-yCsKIcZT-LSxqd1uY8H0NdiCaVeyABwPfcMAo0s4hNyK1znRSQ6BOx-VzAULFKLFRCI4AQvGYBMRoSvDPwiYjTEUasQLc8Tz_hrVMn_3-3cQDJVOdoZkFgVFvel86r6pBg5soTZxNFLAoF8KAjJnnaYvlJyB3lflnK_g0Gt90vuhyBBzAY1X1DYxDkLjqekurDbm0WA5ElT9S2wx3972qZJQPFJoksqg4ZV346LuiAeSSUMhzbm9ZRj1XEi5NzrQd9S22EzLdX5sJ9TqooYKM30QVqyBF6I302PkBDvBLLH46-0hC4U1LIh7AGZDZwIk83xTwgPIpy5zlHAn0scVmbhilsfjkCaj5KMvZC4gTjhDgY4YgXU6-hXdce6cjEOxdS4BrXKTl5hw0B5ZWlsjCM_0_NK22cH_2AgnZ6orvdQs87L1pt9hP4IUeBiVn_CnezYWOAjtlHA1bRcGAxi7wzR5LGCS9kB-JcQW-uGMz8EonMS41DQXO8NKrt2mm0d2EtYN8ZFt74pU1wAQnaHjgtib7OoH16IAqQvJ9v9cHzqc0rZX-Rl419BwCDpK9Jjy15QMYg1WvjSFK8oZ3LT0x0HTtcR9pQ8rWMzUg6KQ4b5LTq2_QBxlotgkEn-VqCAhdlZNtw4DnMcaCaT9Vz_8HfE39GKjujnfYZm8KFFLZ6_L4IVkc7glaJYoSqt-xUJ9EoJjpPgFaGc6JdR2incGdWVVcefSUUWRw.24iVA45Bl0OHMLbntjkk9w&context_code=13278&target_redirect_uri=https%3A%2F%2Fsubmission.springernature.com%2Fnew-submission%2F13278%2F3%3F_gl%3D1*1boev1o*_ga*ODUwODAxODQuMTYxMTUwMzQwMg..*_ga_B3E4QL2TPR*MTcwODUwMzE4NC4xMjUuMS4xNzA4NTAzMjMzLjAuMC4w&context_type=submission&_gl=1*1boev1o*_ga*ODUwODAxODQuMTYxMTUwMzQwMg..*_ga_B3E4QL2TPR*MTcwODUwMzE4NC4xMjUuMS4xNzA4NTAzMjMzLjAuMC4w .
Kind Regards Rajesh Sharma, Associate Professor, Head, Computational Social Science Lab, Institute of Computer Science, University of Tartu, Estonia Group webpage: https://css.cs.ut.ee/ Personal Webpage: https://rajeshsharma.cs.ut.ee/