Wikipedia, rich in entities and events, is an invaluable resource for various knowledge harvesting, extraction and mining tasks. Numerous resources like DBpedia, YAGO and other knowledge bases are based on extracting entity and event based knowledge from it. Online news, on the other hand, is an authoritative and rich source for emerging entities, events and facts relating to existing entities. In this work, we study the creation of entities in Wikipedia with respect to news by studying how entity and event based information flows from news to Wikipedia. We analyze the lag of Wikipedia (based on the revision history of the English Wikipedia) with 20 years of The New York Times dataset (NYT). We model and analyze the lag of entities and events, namely their first appearance in Wikipedia and in NYT, respectively. In our extensive experimental analysis, we find that almost 20 of the external references in entity pages are news articles encoding the importance of news to Wikipedia. Second, we observe that the entity-based lag follows a normal distribution with a high standard deviation, whereas the lag for news-based events is typically very low. Finally, we find that events are responsible for creation of emergent entities with as many as 12 of the entities mentioned in the event page are created after the creation of the event page.
@cite_18: 
@cite_3: Wikipedia was formally launched in 2001, but the first research papers mentioning it appeared only in 2002. Since then it raised a huge amount of interest in the research community. At first mainly the content creation processes and the quality of the content were studied, but later on it was picked up as a valuable source for data mining and for testing. In this paper we present preliminary results that characterize the research done on and using Wikipedia since 2002.
@cite_12: Prior research on Wikipedia has characterized the growth in content and editors as being fundamentally exponential in nature, extrapolating current trends into the future. We show that recent editing activity suggests that Wikipedia growth has slowed, and perhaps plateaued, indicating that it may have come against its limits to growth. We measure growth, population shifts, and patterns of editor and administrator activities, contrasting these against past results where possible. Both the rate of page growth and editor growth has declined. As growth has declined, there are indicators of increased coordination and overhead costs, exclusion of newcomers, and resistance to new edits. We discuss some possible explanations for these new developments in Wikipedia including decreased opportunities for sharing existing knowledge and increased bureaucratic stress on the socio-technical system itself.
goes into similar directions with our analysis. @cite_18 analyses the collaborator structure of Wikipedia. They further classify the collaborators into five different classes based on the number of revisions. Furthermore, they measure the population growth of the collaborators falling into the five different classes. In their paper the authors conclude an interesting observation of the shift of how content is mostly provided by collaborators with lower number of edits, due to the increased fraction of such users in the Wikipedia community structure. This, however, does not correlate with any decline of the content provided by collaborators with high number of edits, hence, is accounted to the higher fraction of low edit users. In contrast to the work from , we have a different focus in our analysis, namely that of entity and event lag in Wikipedia, without any distinction of the Wikipedia community structure. In @cite_12 the authors analyze several aspects of Wikipedia's editors. They conclude that the number of edits is decreasing. Another slightly related work @cite_3 analyzes the number of research papers about Wikipedia, here too they conclude that the number has been decreasing, however, papers that use Wikpedia's data has seen an increase.