CFP for 10th International Workshop on Modeling Social Media (MSM 2019): Mining, Modeling and Learning in Social Media (Deadline: January 10, 2019)
** Please forward to anyone who might be interested ** -------------------------------------------------------------- CALL FOR PAPERS 10th International Workshop on Modeling Social Media (MSM'2019) Mining, Modeling and Learning from Social Media
to be held on May 14-17, 2019, San Francisco, USA co-located with TheWebConf 2019
https://msmworkshop.github.io/ --------------------------------------------------------------
Important Dates: ================ ** Submission Deadline: Jan 10, 2019 ** Notification of Acceptance: Feb 14, 2019 ** Camera-Ready Versions Due: Mar 3, 2019 ** Workshop date: May 13-14, 2019
Workshop Organizers: ==================== Martin Atzmueller, Tilburg University, Netherlands; m.atzmueller@uvt.nl Alvin Chin, BMW Technology Corporation, USA; alvin.chin@bmwna.com Christoph Trattner, University of Bergen, Norway; trattner.christoph@gmail.com
Program Committee: ================== Alejandro Bellogin, Universidad Autonoma de Madrid, Spain Javier Luis Canovas Izquierdo, IN3 - UOC, Spain Michelangelo Ceci, Universita degli Studi di Bari, Italy Michael Granitzer, University of Passau, Germany Bin Guo, Institut Telecom Sud Paris, France Eelco Herder, Radboud University, Netherlands Geert-Jan Houben, Delft University of Technology, Netherlands Ralf Klamma, RWTH Aachen University, Germany Bart Knijnenburg, Clemson University, USA Dominik Kowald, Know-Center, Austria Florian Lemmerich, RWTH Aachen, Germany Nico Piatkowski, AI Group, TU Dortmund, Germany Haggai Roitman, IBM Research Haifa, Israel Giancarlo Ruffo, Universita di Torino, Italy Marc Smith, Connected Action Consulting Group, USA Longqi Yang, Cornell University, USA Arkaitz Zubiaga, The University of Warwick, UK
We aim to attract researchers from all over the world working on data mining, modeling and using machine learning and AI for social media, big and small data, sensor data and the web. Social networks such as Facebook, Twitter, and LinkedIn have paved the way for generating huge amount of diverse, streaming bit data in a short period of time. Such social media data require the application of big data analytics to produce meaningful information to both information consumers and data generators. Machine learning and AI techniques are particularly effective in situations where deep and predictive insights need to be uncovered from such social media data sets that are large, diverse and fast changing. Following the discussion at our workshop at TheWebConf 2018, we aim to focus on how to apply data mining, recommendation, machine learning and AI models, algorithms and systems for analytic and predictive modeling on social media, big data, small data, web and sensor data. Contrary to last year’s workshop, we would like to particularly invite researchers that are interested in going beyond standard analytics approaches and try to discover the intelligent information hidden in the large and fast-changing social media data.
Overall, we are interested in receiving papers related to the following topics which include but are not limited to: * predictive analytics methods or frameworks for social media, big data, small data, sensor data and the web * AI, machine learning, deep learning and NLP models, algorithms and systems for social media, big data, small data, sensor data and the web * deep learning approaches and models for social media, big data, small data, sensor data and data from/on the web * data mining techniques and algorithms for social media, big data, small data, sensor data and data from/on the web * methods for learning social activities and behavioral analytic metrics * evaluation of machine learning and AI frameworks and metrics * explainability and transparency of the machine learning/deep learning/AI methods * applications of machine learning, deep learning and AI * applications of any of the above methods and technologies
The goal of this workshop is to use data mining, machine learning and AI approaches and algorithms on social media, big data, small data, sensor data and data from/on the web.
Submissions: We solicit full research papers (4-8 pages), and short papers (1-4 pages) both in the ACM conference paper style. Papers should be submitted in EasyChair tohttps://easychair.org/my/conference.cgi?conf=msm2019
Proceedings: ============ Contributions will be included in the Companion volume of TheWebConf 2019 conference, which will be published by ACM and included in the ACM Digital Library. However, to make that happen at least one author of the accepted paper has to register. At the time of submission of the final camera-ready copy, authors will have to indicate the already registered person for that publication.
Any paper published by the ACM, IEEE, etc. which can be properly cited constitutes research which must be considered in judging the novelty of a TheWebConf submission, whether the published paper was in a conference, journal, or workshop. Therefore, any paper previously published as part of a WWW or TheWebConf workshop must be referenced and suitably extended with new content to qualify as a new submission to the Research Track at TheWebConf conference.
Submission guidelines: ====================== All submitted papers must * be written in English; * contain author names, affiliations, and email addresses; * be formatted according to the ACM SIG Proceedings template (http://www.acm.org/sigs/publications/proceedings-templates) with a font size no smaller than 9pt; * be in PDF (make sure that the PDF can be viewed on any platform), and formatted for US Letter size; * occupy no more than six pages, including the abstract, references, and appendices.
It is the authors’ responsibility to ensure that their submissions adhere strictly to the required format. Submissions that do not comply with the above guidelines may be rejected without review.
All submissions must be entered into the reviewing system:https://easychair.org/conferences/?conf=msm2019
Contact: ======== Martin Atzmueller, Tilburg University, Netherlands; m.atzmueller@uvt.nl Alvin Chin, BMW Technology Corporation, USA; alvin.chin@bmwna.com Christoph Trattner, University of Bergen, Norway; trattner.christoph@gmail.com
Follow us on: ============= Facebook https://www.facebook.com/groups/527164050627185/ Twitter https://twitter.com/msm_workshop
Dear colleague,
The submission deadline for MSM 2019 workshop has been extended until January 24, 2019.
** Please forward to anyone who might be interested ** -------------------------------------------------------------- CALL FOR PAPERS 10th International Workshop on Modeling Social Media (MSM'2019) Mining, Modeling and Learning from Social Media
to be held on May 14-17, 2019, San Francisco, USA co-located with TheWebConf 2019
https://msmworkshop.github.io/ https://urldefense.proofpoint.com/v2/url?u=https-3A__msmworkshop.github.io_&d=DwMFaQ&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=LeA03ajd0gDQUx100AZl2vXyKx-_71jG6lYVs2J7KL4&s=NFtf5_A9bFIb9VqYaWZVEQT2gcQIYzbkxqUE3bjm3YU&e= --------------------------------------------------------------
Important Dates: ================ ** Submission Deadline: Jan 24, 2019 (EXTENDED) ** Notification of Acceptance: Feb 14, 2019 ** Camera-Ready Versions Due: Mar 3, 2019 ** Workshop date: May 13-14, 2019
Workshop Organizers: ==================== Martin Atzmueller, Tilburg University, Netherlands; m.atzmueller@uvt.nl Alvin Chin, BMW Technology Corporation, USA; alvin.chin@bmwna.com Christoph Trattner, University of Bergen, Norway; trattner.christoph@gmail.com
Program Committee: ================== Alejandro Bellogin, Universidad Autonoma de Madrid, Spain Javier Luis Canovas Izquierdo, IN3 - UOC, Spain Michelangelo Ceci, Universita degli Studi di Bari, Italy Michael Granitzer, University of Passau, Germany Bin Guo, Institut Telecom Sud Paris, France Eelco Herder, Radboud University, Netherlands Geert-Jan Houben, Delft University of Technology, Netherlands Ralf Klamma, RWTH Aachen University, Germany Bart Knijnenburg, Clemson University, USA Dominik Kowald, Know-Center, Austria Florian Lemmerich, RWTH Aachen, Germany Nico Piatkowski, AI Group, TU Dortmund, Germany Haggai Roitman, IBM Research Haifa, Israel Giancarlo Ruffo, Universita di Torino, Italy Marc Smith, Connected Action Consulting Group, USA Longqi Yang, Cornell University, USA Arkaitz Zubiaga, The University of Warwick, UK
We aim to attract researchers from all over the world working on data mining, modeling and using machine learning and AI for social media, big and small data, sensor data and the web. Social networks such as Facebook, Twitter, and LinkedIn have paved the way for generating huge amount of diverse, streaming bit data in a short period of time. Such social media data require the application of big data analytics to produce meaningful information to both information consumers and data generators. Machine learning and AI techniques are particularly effective in situations where deep and predictive insights need to be uncovered from such social media data sets that are large, diverse and fast changing. Following the discussion at our workshop at TheWebConf 2018, we aim to focus on how to apply data mining, recommendation, machine learning and AI models, algorithms and systems for analytic and predictive modeling on social media, big data, small data, web and sensor data. Contrary to last year’s workshop, we would like to particularly invite researchers that are interested in going beyond standard analytics approaches and try to discover the intelligent information hidden in the large and fast-changing social media data.
Overall, we are interested in receiving papers related to the following topics which include but are not limited to: * predictive analytics methods or frameworks for social media, big data, small data, sensor data and the web * AI, machine learning, deep learning and NLP models, algorithms and systems for social media, big data, small data, sensor data and the web * deep learning approaches and models for social media, big data, small data, sensor data and data from/on the web * data mining techniques and algorithms for social media, big data, small data, sensor data and data from/on the web * methods for learning social activities and behavioral analytic metrics * evaluation of machine learning and AI frameworks and metrics * explainability and transparency of the machine learning/deep learning/AI methods * applications of machine learning, deep learning and AI * applications of any of the above methods and technologies
The goal of this workshop is to use data mining, machine learning and AI approaches and algorithms on social media, big data, small data, sensor data and data from/on the web.
Submissions: We solicit full research papers (4-8 pages), and short papers (1-4 pages) both in the ACM conference paper style. Papers should be submitted in EasyChair tohttps://easychair.org/my/conference.cgi?conf=msm2019 https://urldefense.proofpoint.com/v2/url?u=https-3A__easychair.org_my_conference.cgi-3Fconf-3Dmsm2019&d=DwMFaQ&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=LeA03ajd0gDQUx100AZl2vXyKx-_71jG6lYVs2J7KL4&s=X6xAi5Vu8uEWSoT1oPH85br-ZtMXUtoPfU3ZtXH4HyQ&e=
Proceedings: ============ Contributions will be included in the Companion volume of TheWebConf 2019 conference, which will be published by ACM and included in the ACM Digital Library. However, to make that happen at least one author of the accepted paper has to register. At the time of submission of the final camera-ready copy, authors will have to indicate the already registered person for that publication.
Any paper published by the ACM, IEEE, etc. which can be properly cited constitutes research which must be considered in judging the novelty of a TheWebConf submission, whether the published paper was in a conference, journal, or workshop. Therefore, any paper previously published as part of a WWW or TheWebConf workshop must be referenced and suitably extended with new content to qualify as a new submission to the Research Track at TheWebConf conference.
Submission guidelines: ====================== All submitted papers must * be written in English; * contain author names, affiliations, and email addresses; * be formatted according to the ACM SIG Proceedings template (https://www.acm.org/publications/proceedings-template https://urldefense.proofpoint.com/v2/url?u=https-3A__www.acm.org_publications_proceedings-2Dtemplate&d=DwMFaQ&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=LeA03ajd0gDQUx100AZl2vXyKx-_71jG6lYVs2J7KL4&s=2iy9CTdGUAq2F_TYQVX3JmpsnSsjn-qouI8iW1STVgU&e=) with a font size no smaller than 9pt; * be in PDF (make sure that the PDF can be viewed on any platform), and formatted for US Letter size; * occupy no more than six pages, including the abstract, references, and appendices.
It is the authors’ responsibility to ensure that their submissions adhere strictly to the required format. Submissions that do not comply with the above guidelines may be rejected without review.
All submissions must be entered into the reviewing system:https://easychair.org/conferences/?conf=msm2019 https://urldefense.proofpoint.com/v2/url?u=https-3A__easychair.org_conferences_-3Fconf-3Dmsm2019&d=DwMFaQ&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=LeA03ajd0gDQUx100AZl2vXyKx-_71jG6lYVs2J7KL4&s=AOYt8nuNg8q62Ap6HMxmmm-Dcu-B906tJniELdUwqRc&e=
Contact: ======== Martin Atzmueller, Tilburg University, Netherlands; m.atzmueller@uvt.nl Alvin Chin, BMW Technology Corporation, USA; alvin.chin@bmwna.com Christoph Trattner, University of Bergen, Norway; trattner.christoph@gmail.com
Follow us on: ============= Facebook https://www.facebook.com/groups/527164050627185/ https://urldefense.proofpoint.com/v2/url?u=https-3A__www.facebook.com_groups_527164050627185_&d=DwMFaQ&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=LeA03ajd0gDQUx100AZl2vXyKx-_71jG6lYVs2J7KL4&s=pufn0UD0tZlN86PgMX0etT9qgZztW6mG_l7J-rIIc2M&e= Twitter https://twitter.com/msm_workshop https://urldefense.proofpoint.com/v2/url?u=https-3A__twitter.com_msm-5Fworkshop&d=DwMFaQ&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=LeA03ajd0gDQUx100AZl2vXyKx-_71jG6lYVs2J7KL4&s=VP05m4JilLyePUkbsROUcjxtxxDvSaCwyZ5Uk4wBSdY&e=
On Mon, Dec 17, 2018 at 9:03 PM Alvin Chin alvin.chin@utoronto.ca wrote:
** Please forward to anyone who might be interested **
CALL FOR PAPERS10th International Workshop on Modeling Social Media (MSM'2019) Mining, Modeling and Learning from Social Media
to be held on May 14-17, 2019, San Francisco, USA co-located with TheWebConf 2019 https://msmworkshop.github.io/
Important Dates:
** Submission Deadline: Jan 10, 2019 ** Notification of Acceptance: Feb 14, 2019 ** Camera-Ready Versions Due: Mar 3, 2019 ** Workshop date: May 13-14, 2019
Workshop Organizers:
Martin Atzmueller, Tilburg University, Netherlands; m.atzmueller@uvt.nl Alvin Chin, BMW Technology Corporation, USA; alvin.chin@bmwna.com Christoph Trattner, University of Bergen, Norway; trattner.christoph@gmail.com
Program Committee:
Alejandro Bellogin, Universidad Autonoma de Madrid, Spain Javier Luis Canovas Izquierdo, IN3 - UOC, Spain Michelangelo Ceci, Universita degli Studi di Bari, Italy Michael Granitzer, University of Passau, Germany Bin Guo, Institut Telecom Sud Paris, France Eelco Herder, Radboud University, Netherlands Geert-Jan Houben, Delft University of Technology, Netherlands Ralf Klamma, RWTH Aachen University, Germany Bart Knijnenburg, Clemson University, USA Dominik Kowald, Know-Center, Austria Florian Lemmerich, RWTH Aachen, Germany Nico Piatkowski, AI Group, TU Dortmund, Germany Haggai Roitman, IBM Research Haifa, Israel Giancarlo Ruffo, Universita di Torino, Italy Marc Smith, Connected Action Consulting Group, USA Longqi Yang, Cornell University, USA Arkaitz Zubiaga, The University of Warwick, UK
We aim to attract researchers from all over the world working on data mining, modeling and using machine learning and AI for social media, big and small data, sensor data and the web. Social networks such as Facebook, Twitter, and LinkedIn have paved the way for generating huge amount of diverse, streaming bit data in a short period of time. Such social media data require the application of big data analytics to produce meaningful information to both information consumers and data generators. Machine learning and AI techniques are particularly effective in situations where deep and predictive insights need to be uncovered from such social media data sets that are large, diverse and fast changing. Following the discussion at our workshop at TheWebConf 2018, we aim to focus on how to apply data mining, recommendation, machine learning and AI models, algorithms and systems for analytic and predictive modeling on social media, big data, small data, web and sensor data. Contrary to last year’s workshop, we would like to particularly invite researchers that are interested in going beyond standard analytics approaches and try to discover the intelligent information hidden in the large and fast-changing social media data.
Overall, we are interested in receiving papers related to the following topics which include but are not limited to:
- predictive analytics methods or frameworks for social media, big data, small data, sensor data and the web
- AI, machine learning, deep learning and NLP models, algorithms and systems for social media, big data, small data, sensor data and the web
- deep learning approaches and models for social media, big data, small data, sensor data and data from/on the web
- data mining techniques and algorithms for social media, big data, small data, sensor data and data from/on the web
- methods for learning social activities and behavioral analytic metrics
- evaluation of machine learning and AI frameworks and metrics
- explainability and transparency of the machine learning/deep learning/AI methods
- applications of machine learning, deep learning and AI
- applications of any of the above methods and technologies
The goal of this workshop is to use data mining, machine learning and AI approaches and algorithms on social media, big data, small data, sensor data and data from/on the web.
Submissions: We solicit full research papers (4-8 pages), and short papers (1-4 pages) both in the ACM conference paper style. Papers should be submitted in EasyChair tohttps://easychair.org/my/conference.cgi?conf=msm2019
Proceedings:
Contributions will be included in the Companion volume of TheWebConf 2019 conference, which will be published by ACM and included in the ACM Digital Library. However, to make that happen at least one author of the accepted paper has to register. At the time of submission of the final camera-ready copy, authors will have to indicate the already registered person for that publication.
Any paper published by the ACM, IEEE, etc. which can be properly cited constitutes research which must be considered in judging the novelty of a TheWebConf submission, whether the published paper was in a conference, journal, or workshop. Therefore, any paper previously published as part of a WWW or TheWebConf workshop must be referenced and suitably extended with new content to qualify as a new submission to the Research Track at TheWebConf conference.
Submission guidelines:
All submitted papers must * be written in English; * contain author names, affiliations, and email addresses; * be formatted according to the ACM SIG Proceedings template (http://www.acm.org/sigs/publications/proceedings-templates) with a font size no smaller than 9pt; * be in PDF (make sure that the PDF can be viewed on any platform), and formatted for US Letter size; * occupy no more than six pages, including the abstract, references, and appendices.
It is the authors’ responsibility to ensure that their submissions adhere strictly to the required format. Submissions that do not comply with the above guidelines may be rejected without review.
All submissions must be entered into the reviewing system:https://easychair.org/conferences/?conf=msm2019
Contact:
Martin Atzmueller, Tilburg University, Netherlands; m.atzmueller@uvt.nl Alvin Chin, BMW Technology Corporation, USA; alvin.chin@bmwna.com Christoph Trattner, University of Bergen, Norway; trattner.christoph@gmail.com
Follow us on:
Facebook https://www.facebook.com/groups/527164050627185/ Twitter https://twitter.com/msm_workshop
computational.science@lists.iccsa.org
-
Alvin Chin