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BroDyn 2018 : 1st International Workshop on Analysis of Broad Dynamic Topics over Social Media (Co-located with ECIR 2018)

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Link: https://sites.google.com/view/brodyn2018
 
When Mar 26, 2081 - Mar 26, 2081
Where Grenoble, France
Submission Deadline Jan 15, 2018
Notification Due Feb 15, 2018
Final Version Due Feb 26, 2018
Categories    information retrieval   social media   topic tracking   data analytics
 

Call For Papers

You are invited to submit your research work to the 1st International Workshop on Analysis of Broad Dynamic Topics over Social Media (BroDyn ’18), to be held at Grenoble, France, on March 26th 2018, in conjunction with the 40th European Conference on Information Retrieval (ECIR 2018).

Find more information on our website (https://sites.google.com/view/brodyn2018) and follow us on Twitter @BroDyn2018.

**Motivation and Overview
In recent years, users developed a widespread perception of social media as news sources that they follow (almost all day long) to get updated on their topics of interest. Many of those topics attract long-standing user interest (i.e., span or stay active for long period of time), are very broad (i.e., cover many aspects or subtopics), and are dynamic (i.e., develop and change focus over time with subtopics becoming obsolete over time and new subtopics emerge). Such kind of broad and dynamic topics can run for few weeks, such as crisis events (e.g., “Hurricane Irma”), or up to years, such as “the Syrian conflict”. Other examples of broad dynamic topics include “Refugees in Europe”, “Qatar Crisis”, “Brexit”, “North Korea and US conflict” to name a few.
Effective exploitation of content posted on social media that is relevant to broad dynamic topics requires adaptive techniques to effectively capture the different and changing aspects of the topics. The techniques should also be scalable to cope with the large volume of posts and the diversity of the sub-topics, real-time to be responsive to the high velocity of the data, and reliable to perform effectively over the long duration of the topic. In addition to that, new evaluation frameworks for such domain are also needed with novel evaluation measures that capture the nature of topics (and thus systems) and new large reusable datasets that enable the researchers to run meaningful and representative experiments.
The workshop aims to bring together audience at all levels, including researchers from academia and industry as well as potential users, to create a forum for discussing recent advances in this emerging area. The theme of the workshop concerns, besides IR and social computing researchers, a wide spectrum of potential users of the needed technology, such as journalists, historians, politicians, social scientists and analysts.

**Workshop Aims
BroDyn workshop aims to achieve the following objectives:
1. Directing the attention of IR researchers to the new emerging type of information needs that require following broad and dynamic topics and events over social media streams.
2. Better understanding of the limitations of the current methods and inspiring research on new algorithms and techniques.
3. Encouraging the design of new evaluation measures, datasets, and test collections to support the research in that area.
4. Forming a new community that brings together IR and social computing researchers as well as potential users who are interested in the domain.

**Topics of Interest
We encourage submissions on all topics related to the theme of analysis of broad and dynamic topics over social media, focused on (but not limited to) the following tasks:
- Adaptive high-recall high-precision filtering / topic tracking
- Adaptive summarization
- Topic/sub-topic or event/sub-event detection over time
- Retrospective generation of timelines
- Following controversial political events/crises: identification of decision makers, credibility/information source finding, stance/opinion mining, troll detection, fact checking
- Cross-media filtering (i.e., over heterogeneous sources)
- Multilingual topic/event detection
- Online/dynamic topic modeling
- Real-time/scalable techniques of processing high-volume streams
- Evaluation techniques and novel test collections (specific for broad dynamic topics)
- Spam and hashtag-spam detection
- Bot and automatically-generated content detection
- Data visualization
- Recommendation (e.g., of hashtags/topics/sub-topics)
- Learning techniques/deep learning over social streams

**Available Datasets
We encourage (but not require) submissions describing experiments using the GE2017 (a dataset of around 18M tweets on the British General Elections 2017) and/or USPresElect2016 (a dataset of 3,450 labelled tweets on the US Presidential Elections 2016). Find more details on our website.

**Submissions
We are seeking the submission of full and short papers, representing original research, preliminary research results, proposals for new work, and position and opinion papers. All submitted papers will be peer-reviewed through double-blind reviewing process.
Accepted papers will be published in the workshop proceedings, and will have to be presented at the workshop either as an oral presentation or as a poster. At least one author of each accepted paper is expected to register and attend the workshop to present the paper.
All submissions must be written in English following the LNCS author guidelines. Full papers must not exceed 12 pages and short papers must not exceed 6 pages, including figures and references. Papers should be submitted as PDF files electronically through EasyChair.

Important Dates
- Full and short papers submission: 15 January 2018 (midnight AoE)
- Notification of acceptance: 15 February 2018
- Camera ready submission: 26 February 2018 (midnight AoE)
- DroDyn Workshop: 26 March 2018
- ECIR Conference: 26-29 March 2018

Organizing Committee
- Tamer Elsayed, Qatar University, Qatar
- Walid Magdy, University of Edinburgh, UK
- Mucahid Kutlu, Qatar University, Qatar
- Maram Hasanain, Qatar University, Qatar
- Reem Suwaileh, Qatar University, Qatar

For any inquiries, contact us: telsayed@qu.edu.qa, wmagdy@inf.ed.ac.uk

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