A twenty-first century science

By Duncan J. Watts. Nature, 2007

330 citations recorded by the source corpus.

Subfields: Management Information Systems

View Paper: https://www.semanticscholar.org/paper/75974013b5abee21298e7119964cf4e8965f16de

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In Management Information Systems

Citations in the corpus

Beyond Word Frequency: Bursts, Lulls, and Scaling in the Temporal Distributions of Words (2009, background): “With the rise of the Internet, large records of spontaneous and collective language are now available for scientific inquiry [22, 23, 24], allowing statistical questions about language to be investigated with an unprecedented precision.”
Three maps and three misunderstandings: A digital mapping of climate diplomacy (2014, background): “While optimists welcome enthusiastically a new source of information, potentially richer and less expensive than traditional datasets (Kleinberg, 2008; Watts, 2007), pessimists show distrust towards the turmoil caused by a flood of muddled traces.”
Analyzing and modeling real-world phenomena with complex networks: a survey of applications (2007, background): “Both types of approaches have benefited from the increase of World Wide Web popularity [76, 77].”
Dynamic population mapping using mobile phone data (2014, background): “Data provided by communication tools are opening up new opportunities for studying sociospatial behaviors (33 – 36).”
A Poissonian explanation for heavy tails in e-mail communication (2008, neutral): “Our model further suggests a novel experiment [36] which not only records when an individual has sent an e-mail, but also w hen that individual is using a computer or actively utilizing an e-mail client.”
Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees (2011, background): “New technologies are now available that allow the tracking of proximity to and interactions between individuals [28-37], greatly transforming our ability to understand and characterize social behavior [38].”
Detecting weak and strong Islamophobic hate speech on social media (2018, background): “, 2009), Watts argues that big data can provide insight into age-old questions by “mak[ing] visible social processes that are much more difficult to study in conventional organizational settings” (Watts, 2007) and in political science Grimmer and Stewart argue that “automated content methods can mak”
Validity Issues in the Use of Social Network Analysis with Digital Trace Data (2011, neutral): “The availability of such trace data, together with exciting domains and an appropriate analysis technique, form a golden opportunity for research, perhaps even a “21 st Century Science” (Watts, 2007).”
Novelty and collective attention (2007, background): “These experiments, which complement large social network studies of viral marketing [7] are facilitated by the availability of websites that attract millions of users, a fact that turns the internet into an interesting natural laboratory for testing and discovering the behavioral patterns of large p”
What's in a crowd? Analysis of face-to-face behavioral networks (2010, background): “…of complex networks (Anon, 2009; Dorogovtsev and Mendes, 2003; Newman, 2003; Pastor-Satorras and Vespignani, 2004; Caldarelli, 2007; Barrat et al., 2008; Wasserman and Faust, 1994; Watts, 2007) has led to many research efforts because of the naturally inter-linked nature of these new data sources.”
New Insights into Rental Housing Markets across the United States: Web Scraping and Analyzing Craigslist Rental Listings (2016, background): “Big data are starting to have a paradigm-shifting impact on social science research, and data from Internet-based interactions have the potential to reshape our understanding of collective human dynamics (Watts 2007; Batty et al. 2012).”
Recommender Systems (2012, background): “Traditional ‘‘soft sciences’’, such as sociology or economics, have their fast-growing branches relying on the study of these newly available massive data sets [1,2].”
Collaborative Filtering beyond the User-Item Matrix (2014, background): “Next, the presence of various sources of situational information (also referred to as contexts in the literature) that are associated with the U-I interactions gives rise to three additional groups of algorithms that can be distinguished on the basis of the underlying approach they choose: TF,…”