P. Mike’s scientific contributions

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Publications (1)


Figure 1. Three sources of term definition.
Table 3 . Top 10 empirical properties of foaf:Person in DS-SWOOGLE.
Table 4 . Top 10 empirical properties of foaf:Person in DS-FOAF-VAR.
Figure 6. The resulting community ontology is the result of folding Figure 5's bipartite graph and normalizing the weights using geometric normalization.
Social Networks Applied
  • Article
  • Full-text available

February 2005

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399 Reads

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259 Citations

Intelligent Systems, IEEE

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P. Mike

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Social networks have interesting properties. They influence our lives enormously without us being aware of the implications they raise. The authors investigate the following areas concerning social networks: how to exploit our unprecedented wealth of data and how we can mine social networks for purposes such as marketing campaigns; social networks as a particular form of influence, i.e.., the way that people agree on terminology and this phenomenon's implications for the way we build ontologies and the Semantic Web; social networks as something we can discover from data; the use of social network information to offer a wealth of new applications such as better recommendations for restaurants, trustworthy email senders, or (maybe) blind dates; investigation of the richness and difficulty of harvesting FOAF (friend-of-a-friend) information; and by looking at how information processing is bound to social context, the resulting ways that network topology's definition determines its outcomes.

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Citations (1)


... The degree of influence a social media user has on their friends, as well as their desire to spread additional information, can be detected from interest similarity. Authors have submitted that people users are more affected and influenced by their friends' opinions than by other influencers Domingos and Richardson (2001); Staab et al. (2005). In Xie et al. (2014), the measure of similarity between two users is based on a random walk distance based on tags and image correlation and was examined in folksonomy data. ...

Reference:

A Survey on Social Media Influence Environment and Influencers Identification
Social Networks Applied

Intelligent Systems, IEEE