A fundamental open question in the analysis of social networks is to understand the interplay between similarity and social ties. People are similar to their neighbors in a social network for two distinct reasons: first, they grow to resemble their current friends due to social influence; and second, they tend to form new links to others who are already like them, a process often termed selection by sociologists. While both factors are present in everyday social processes, they are in tension: social influence can push systems toward uniformity of behavior, while selection can lead to fragmentation. As such, it is important to understand the relative effects of these forces, and this has been a challenge due to the difficulty of isolating and quantifying them in real settings.

@inproceedings{crandall2008feedback, author = {Crandall, David and Cosley, Dan and Huttenlocher, Daniel and Kleinberg, Jon and Suri, Siddharth}, title = {Feedback effects between similarity and social influence in online communities}, booktitle = {KDD '08: Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining}, publisher = {ACM}, address = {New York, NY, USA}, year = {2008}, pages = {160--168}, url = {http://dx.doi.org/10.1145/1401890.1401914}, doi = {10.1145/1401890.1401914}, isbn = {978-1-60558-193-4}, keywords = {feedback, tagging, social, feedback_effects, similarity, toread, social_communities}, abstract = {A fundamental open question in the analysis of social networks is to understand the interplay between similarity and social ties. People are similar to their neighbors in a social network for two distinct reasons: first, they grow to resemble their current friends due to social influence; and second, they tend to form new links to others who are already like them, a process often termed selection by sociologists. While both factors are present in everyday social processes, they are in tension: social influence can push systems toward uniformity of behavior, while selection can lead to fragmentation. As such, it is important to understand the relative effects of these forces, and this has been a challenge due to the difficulty of isolating and quantifying them in real settings.} }

%0 = inproceedings %A = Crandall, David and Cosley, Dan and Huttenlocher, Daniel and Kleinberg, Jon and Suri, Siddharth %B = KDD '08: Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining %C = New York, NY, USA %D = 2008 %I = ACM %T = Feedback effects between similarity and social influence in online communities %U = http://dx.doi.org/10.1145/1401890.1401914

@inproceedings{bollegala2007measuring, author = {Bollegala, Danushka and Matsuo, Yutaka and Ishizuka, Mitsuru}, title = {Measuring semantic similarity between words using web search engines}, booktitle = {WWW '07: Proceedings of the 16th international conference on World Wide Web}, publisher = {ACM}, address = {New York, NY, USA}, year = {2007}, pages = {757--766}, url = {http://www2007.org/papers/paper632.pdf}, doi = {http://doi.acm.org/10.1145/1242572.1242675}, isbn = {978-1-59593-654-7}, keywords = {words, terms, similarity, semantic, web, toread, search_engine} }

%0 = inproceedings %A = Bollegala, Danushka and Matsuo, Yutaka and Ishizuka, Mitsuru %B = WWW '07: Proceedings of the 16th international conference on World Wide Web %C = New York, NY, USA %D = 2007 %I = ACM %T = Measuring semantic similarity between words using web search engines %U = http://www2007.org/papers/paper632.pdf

Ontologies are widely used and play important roles in applications related to knowledge management, artificial intelligence, natural language processing, etc. Measuring the semantic similarity between ontological concepts is necessary in applications that use ontologies. This paper presents a survey of approaches to compute ontological concept similarity. A taxonomy showing the classification of approaches is introduced. The advantages and disadvantages of each approach are discussed.

@inproceedings{le2007current, author = {Le, Duy Ngan and Goh, A.E.S.}, title = {Current Practices in Measuring Ontological Concept Similarity}, journal = {Semantics, Knowledge and Grid, Third International Conference on}, year = {2007}, pages = {266-269}, doi = {10.1109/SKG.2007.16}, keywords = {concept, similarity, toread, ontology}, abstract = {Ontologies are widely used and play important roles in applications related to knowledge management, artificial intelligence, natural language processing, etc. Measuring the semantic similarity between ontological concepts is necessary in applications that use ontologies. This paper presents a survey of approaches to compute ontological concept similarity. A taxonomy showing the classification of approaches is introduced. The advantages and disadvantages of each approach are discussed.} }

%0 = inproceedings %A = Le, Duy Ngan and Goh, A.E.S. %D = 2007 %T = Current Practices in Measuring Ontological Concept Similarity

@article{malt1999knowing, author = {Malt, B.C. and Sloman, S.A. and Gennari, S. and Shi, M. and Wang, Y.}, title = {Knowing versus naming: Similarity and the linguistic categorization of artifacts}, journal = {Journal of Memory and Language}, publisher = {Citeseer}, year = {1999}, volume = {40}, pages = {230--262}, url = {http://scholar.google.de/scholar.bib?q=info:43NPl_inXfsJ:scholar.google.com/&output=citation&hl=de&as_sdt=2000&as_vis=1&ct=citation&cd=0}, issn = {0749-596X}, keywords = {similarity, toread, categorization} }

%0 = article %A = Malt, B.C. and Sloman, S.A. and Gennari, S. and Shi, M. and Wang, Y. %D = 1999 %I = Citeseer %T = Knowing versus naming: Similarity and the linguistic categorization of artifacts %U = http://scholar.google.de/scholar.bib?q=info:43NPl_inXfsJ:scholar.google.com/&output=citation&hl=de&as_sdt=2000&as_vis=1&ct=citation&cd=0