Extracting Event-Related Information from Article Updates in Wikipedia

Géorgescu, Mihai; Kanhabua, Nattiya; Krause, Daniel; Nejdl, Wolfgang; Siersdorfer, Stefan

doi:10.1007/978-3-642-36973-5_22

Cited by 32 publications

(20 citation statements)

References 18 publications

(12 reference statements)

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“…Previous works have investigated the effects of external events on the activity of Wikipedia editors and on the number of pageviews [53,54]. More generally, the characterization of the usage of Wikipedia as a source of information and as a proxy for measuring the global attention to real-world events has been studied [24,38,55,56]. The results of our study add further evidence of the value of Wikipedia data in the field of digital epidemiology, especially for capturing information seeking behavior, and attention patterns during disease outbreaks [57].…”

Section: Discussionmentioning

confidence: 99%

The impact of news exposure on collective attention in the United States during the 2016 Zika epidemic

et al. 2020

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In recent years, many studies have drawn attention to the important role of collective awareness and human behaviour during epidemic outbreaks. A number of modelling efforts have investigated the interaction between the disease transmission dynamics and human behaviour change mediated by news coverage and by information spreading in the population. Yet, given the scarcity of data on public awareness during an epidemic, few studies have relied on empirical data. Here, we use fine-grained, geo-referenced data from three online sources-Wikipedia, the GDELT Project and the Internet Archive-to quantify populationscale information seeking about the 2016 Zika virus epidemic in the U.S., explicitly linking such behavioural signal to epidemiological data. Geo-localized Wikipedia pageview data reveal that visiting patterns of Zika-related pages in Wikipedia were highly synchronized across the United States and largely explained by exposure to national television broadcast. Contrary to the assumption of some theoretical epidemic models, news volume and Wikipedia visiting patterns were not significantly correlated with the magnitude or the extent of the epidemic. Attention to Zika, in terms of Zika-related Wikipedia pageviews, was high at the beginning of the outbreak, when public health agencies raised an international alert and triggered media coverage, but subsequently exhibited an activity profile that suggests nonlinear dependencies and memory effects in the relation between information seeking, media pressure, and disease dynamics. This calls for a new and more general modelling framework to describe the interaction between media exposure, public awareness and disease dynamics during epidemic outbreaks. Data Availability Statement: Data are available from the Zenodo repository (https://doi.org/10. 5281/zenodo.3603916).data, and we compare it with mentions of Zika in US news outlets and TV shows. We also compare the collective attention received by the outbreak with the incidence of Zika reported by the US Centers for Disease Control and Prevention in each state. We find that the attention dynamics was highly synchronized across states, irrespective of the local risk of transmission of the virus. By building a linear regression model, we show that the dynamics of collective attention is highly predictable, even at state level, only based on the national media coverage received by the outbreak. PLOS COMPUTATIONAL BIOLOGYNews exposure and collective attention during epidemics PLOS Computational Biology | https://doi.org/10.

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Section: Discussionmentioning

confidence: 99%

The impact of news exposure on collective attention in the United States during the 2016 Zika epidemic

et al. 2020

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“…A recent work [15] was able to extract event-related information using a system that its first building block is a burst detection component.…”

Section: Identifying Dynamic Patterns In Wikipediamentioning

confidence: 99%

“…The dynamics of Wikipedia edit collaborations have been heavily researched [9]- [15]. The vast majority of edits appears in what is termed an "edit-stream", in which the collaborators keep editing the article until a consensus is reached.…”

Section: Introductionmentioning

confidence: 99%

On Skewed Distributions and Straight Lines

Mokryn

Reznik

2015

Proceedings of the 24th International Conference on World Wide Web

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In this paper, we present a hypothesis that power laws are found only in datasets sampled from a static data, in which each and every item has gained its maximal importance and is not in the process of changing it during the sampling period. We motivate our hypothesis by examining languages, and word-ranking distribution as it appears in books, and in the Bible. To demonstrate the validity of our hypothesis, we experiment with the Wikipedia edit collaboration network. We find that the dataset fits a skewed distribution. Next, we identify its dynamic part. We then show that when the modified part is removed from the obtained dataset, the remaining static part exhibits a good fit to a power law distribution.

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“…The emphasis of that work, however, is the construction of an event model, whereas we are focused on providing a historical corpus for researchers; thus, the "low quality" of a citizen-created archive might be an advantage in our case. Similarly, the work of Georgescu et al [4] in event-model extraction used Wikipedia edits for event detection, concluding that the citizen-generated approach is promising.…”

Section: Background and Related Workmentioning

confidence: 93%

Content Selection and Curation for Web Archiving

Milligan

Ruest

Lin

2016

Proceedings of the 16th ACM/IEEE-CS on Joint Conference on Digital Libraries

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Any preservation effort must begin with an assessment of what content to preserve, and web archiving is no different. There have historically been two answers to the question "what should we archive?" The Internet Archive's broad entire-web crawls have been supplemented by narrower domain-or topic-specific collections gathered by numerous libraries. We can characterize this as content selection and curation by "gatekeepers". In contrast, we have witnessed the emergence of another approach driven by "the masses"-we can archive pages that are contained in social media streams such as Twitter. The interesting question, of course, is how these approaches differ. We provide an answer to this question in the context of a case study about the 2015 Canadian federal elections. Based on our analysis, we recommend a hybrid approach that combines an effort driven by social media and more traditional curatorial methods.

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Extracting Event-Related Information from Article Updates in Wikipedia

Cited by 32 publications

References 18 publications

The impact of news exposure on collective attention in the United States during the 2016 Zika epidemic

The impact of news exposure on collective attention in the United States during the 2016 Zika epidemic

On Skewed Distributions and Straight Lines

Content Selection and Curation for Web Archiving

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