Onomastics is "the science or study of the origin and forms of proper names
persons or places." ["Onomastics". Merriam-Webster.com, 2013.
tp://www.merriam-webster.com (11 February 2013)]. Especially personal names
ay an important role in daily life, as all over the world future parents are
cing the task of finding a suitable given name for their child. This choice
influenced by different factors, such as the social context, language,
ltural background and, in particular, personal taste.
With the rise of the Social Web and its applications, users more and more
teract digitally and participate in the creation of heterogeneous,
stributed, collaborative data collections. These sources of data also reflect
rrent and new naming trends as well as new emerging interrelations among
mes.
The present work shows, how basic approaches from the field of social network
alysis and information retrieval can be applied for discovering relations
ong names, thus extending Onomastics by data mining techniques. The
nsidered approach starts with building co-occurrence graphs relative to data
om the Social Web, respectively for given names and city names. As a main
sult, correlations between semantically grounded similarities among names
.g., geographical distance for city names) and structural graph based
milarities are observed.
The discovered relations among given names are the foundation of "nameling"
ttp://nameling.net], a search engine and academic research platform for given
mes which attracted more than 30,000 users within four months,
derpinningthe relevance of the proposed methodology.