TimeMachine: Entity-Centric Search and Visualization of News Archives

Saleiro, Pedro; Teixeira, Jorge; Soares, Carlos; Oliveira, Eugénio

doi:10.1007/978-3-319-30671-1_78

Cited by 11 publications

(4 citation statements)

References 5 publications

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“…In general, building good 'entity-centric search' tools for analyzing and mining such 'heterogeneous' data and concepts on the Web (not necessarily coming from the sex trade or other unusual domains) have occupied a significant niche in the AI and Information Retrieval literature. A representative (and non-exhaustive) set of references from entity-centric search and data integration literature includes (Hogan et al 2007;Lin et al 2012;Saleiro et al 2016;Tonon et al 2012), and Doan et al (2012). Other relevant work include Fox-Brewster (2015) (providing details on the DARPA MEMEX program, which took a closer look at human trafficking and funded several works cited above), (covering information extraction in illicit Web domains; in particular, human trafficking), Edelman and Stemler (2019) (which considers federal limitations on regulating online marketplaces), Harrendorf et al (2010) (which provides international statistics on crime and justice), Tong et al (2017) (which seeks to semi-automatically detect human trafficking in Web ads through multimodal deep learning), Burbano and Hernandez-Alvarez (2017) (which, similar to the work in Tong et al (2017), attempts to identify human trafficking patterns online through computational means), Kejriwal and Kapoor (2019) (which also uses network science, but as a means for understanding noise in information extracted from sex advertisements, rather than for analysis of the underlying social system itself ) and Kapoor et al (2017) (which uses Artificial Intelligence techniques to correctly extract and identify locations in sex advertisements).…”

Section: Online Sex Markets and Artificial Intelligencementioning

confidence: 99%

Network-theoretic modeling of complex activity using UK online sex advertisements

Kejriwal

2020

Appl Netw Sci

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Online sex has become a fast-growing business in both developing and developed network, with advertisements of (not necessarily unique) individuals numbering in the hundreds of millions across different Web portals. One such major hub of sex advertisement activity, before it was shut down by US federal agencies, was backpage.com. The backpage.com website was a classifieds-advertising portal that had become the largest marketplace for buying and selling sex by the time that federal law enforcement agencies seized it in April 2018. Since then, investigations have been actively underway. However, the data (which has recently been made available to us for research on UK Backpage) also offers valuable insights into the nature of the online sex business, including complex properties that can be best studied using network science. One of the challenges, however, is a rigorous modeling of the data as a network, since the primary data are web advertisements and metadata (backend database) on accounts that posted that ad. In this article, we conduct an empirical study of an important sample of the online sex marketplace using UK backpage, including presenting a methodology for constructing simple 'activity networks' that define some notion of real-world collaboration or connection between two entities (in our case, at the level of ad-posting accounts) and then studying the properties of these networks. We gather a set of insights into a domain that has not been studied at scale, let alone a national level, but that is continuing to be a growing social problem for many countries.

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Section: Online Sex Markets and Artificial Intelligencementioning

confidence: 99%

Network-theoretic modeling of complex activity using UK online sex advertisements

Kejriwal

2020

Appl Netw Sci

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“…Recent work [4] presents a timemachine for Portuguese news. The results of their work are presented as an interactive web tool allowing searching and visualising news stories.…”

Section: Related Workmentioning

confidence: 99%

Towards Entity Timeline Analysis in Polish Political News

Baraniak

Sydow

2018

Studies in Big Data

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Our work presents a simple method of analysing occurrences of entities in news articles. We demonstrate that frequency of named entities in news articles is a reflection of events in real world related to these entities. Occurrences and co-occurrences of entities between portals were compared. We made visualisation of entities frequency in a timeline which can be used to analyse the history of entity occurrences.

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“…Latest events are covered and commented by both parties in a continuous basis through the social media, such as Twitter. When sharing or commenting news on social media, users tend to mention the most predominant entities mentioned in the news story [1]. Therefore, entities, such as personalities, organizations, companies or geographic locations, can act as latent interlinks between online news and social media.…”

Section: Introductionmentioning

confidence: 99%

Learning from the News: Predicting Entity Popularity on Twitter

Saleiro

Soares

2016

Lecture Notes in Computer Science

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Abstract. In this work, we tackle the problem of predicting entity popularity on Twitter based on the news cycle. We apply a supervised learning approach and extract four types of features: (i) signal, (ii) textual, (iii) sentiment and (iv) semantic, which we use to predict whether the popularity of a given entity will be high or low in the following hours. We run several experiments on six different entities in a dataset of over 150M tweets and 5M news and obtained F1 scores over 0.70. Error analysis indicates that news perform better on predicting entity popularity on Twitter when they are the primary information source of the event, in opposition to events such as live TV broadcasts, political debates or football matches.

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TimeMachine: Entity-Centric Search and Visualization of News Archives

Cited by 11 publications

References 5 publications

Network-theoretic modeling of complex activity using UK online sex advertisements

Network-theoretic modeling of complex activity using UK online sex advertisements

Towards Entity Timeline Analysis in Polish Political News

Learning from the News: Predicting Entity Popularity on Twitter

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