Workshop on social media analytics, Washington DC, US
25 July 2010 - 25 July 2010
United States
A workshop on social media analytics will take place on 25 July 2010 in Washington DC, US.
The growth of online social media presents many new opportunities and challenges to producers and consumers of information. Though there is a vast quantity of information available, the consequent challenge is to analyse the large volumes of user-generated content and the implicit (or explicit) links between users, in order to find meaningful insights.
The goal of this workshop is to formalise and address meaningful metrics and predictive tasks, as well as actionable explanatory analysis. This event will bring together researchers from academia, industry and the government, and will be a forum for discussing recent advances in analysis of social media, the practical requirements of the domain and research on new algorithms and techniques for social media analytics.
The workshop will also look to address such questions as:
- 'Given the massive amount of user-generated content on the Web, how can one identify the subset of content (blogs, forums, etc.) that are discussing not only a specific entity, but higher level concepts that are in some way relevant to the product/brand/entity of interest?',
- 'Having identified this subset of relevant content, how does one identify the most authoritative or influential authors in this space?',
- 'How to detect and characterize specific sentiment expressed about an entity (e.g. product) mentioned in a blog or forum?',
- 'How to identify emerging topics of discussion from the constant chatter in the blogosphere and other social media?',
- 'How to overcome the information overload and provide a rich and coherent user experience?',
- 'How to deal with unreliable and often conflicting information?'.
The event will be held at the same time as the 16th Association for Computing Machinery Special Interest Group on Knowledge Discovery and Data Mining International Conference on Knowledge Discovery and Data Mining.For further information on registration, please visit:
http://snap.stanford.edu/soma2010/(opens in new window)
The growth of online social media presents many new opportunities and challenges to producers and consumers of information. Though there is a vast quantity of information available, the consequent challenge is to analyse the large volumes of user-generated content and the implicit (or explicit) links between users, in order to find meaningful insights.
The goal of this workshop is to formalise and address meaningful metrics and predictive tasks, as well as actionable explanatory analysis. This event will bring together researchers from academia, industry and the government, and will be a forum for discussing recent advances in analysis of social media, the practical requirements of the domain and research on new algorithms and techniques for social media analytics.
The workshop will also look to address such questions as:
- 'Given the massive amount of user-generated content on the Web, how can one identify the subset of content (blogs, forums, etc.) that are discussing not only a specific entity, but higher level concepts that are in some way relevant to the product/brand/entity of interest?',
- 'Having identified this subset of relevant content, how does one identify the most authoritative or influential authors in this space?',
- 'How to detect and characterize specific sentiment expressed about an entity (e.g. product) mentioned in a blog or forum?',
- 'How to identify emerging topics of discussion from the constant chatter in the blogosphere and other social media?',
- 'How to overcome the information overload and provide a rich and coherent user experience?',
- 'How to deal with unreliable and often conflicting information?'.
The event will be held at the same time as the 16th Association for Computing Machinery Special Interest Group on Knowledge Discovery and Data Mining International Conference on Knowledge Discovery and Data Mining.For further information on registration, please visit:
http://snap.stanford.edu/soma2010/(opens in new window)