Modeling Information Diffusion in Social Media as Provenance with W3C PROV

Abstract

In recent years, research in information diffusion in social media has attracted a lot of attention, since the produced data is fast, massive and viral. Additionally, the provenance of such data is equally important because it helps to judge the relevance and trustworthiness of the information enclosed in the data. However, social media currently provide insufficient m echanisms f or provenance, while models of information diffusion use their own concepts and notations, targeted to specific use cases. In this paper, we propose a model for information diffusion and provenance, based on the W3C PROV Data Model. The advantage is that PROV is a Web-native and interoperable format that allows easy publication of provenance data, and minimizes the integration effort among different systems making use of PROV.

Detecting misinformation in social networks using provenance data

“…We construct the fuzzy pair-wise comparison matrix using the Buckley's fuzzy geometric mean method algorithm (2) and based on the transformed TFNs shown in Table 1. Table 4 illustrates the fuzzy pair-wise comparison matrix at the criteria level.…”

“…Understanding the propagation of information on social media gives users additional context relating to the origin of information they encounter and any modifications it may have undergone while transitioning from user to user. Normal social media users leverage such information in order to evaluate the trustworthiness and validity of information they encounter . In this paper, we argue that the quality of information created on social networks can be determined through its provenance.…”

An approach to custom privacy policy violation detection problems using big social provenance data

“…He argued the value of such information in evaluating users' published information quality. Meanwhile, some have argued that not only user‐related metadata are worth looking at but also the way in which data are propagated may also indicate their value, trust, and validity …”

A Model of Provenance Applied to Biodiversity Datasets

“…Some of these research institutions are: the Global Biodiversity Information Facility 1 (GBIF), the Biodiversity Database Collection of the National Research Institute for the Amazon 2 (INPA), the Large-Scale Biosphere-Atmosphere Experiment in Amazonia 3 (LBA), the Reference Center on Environmental Information 4 (CRIA), and the New York Botanical Garden 5 (NYBG). While most researches in biodiversity pay much attention to the generation of biodiversity datasets and Web access, information that specifies how/where these data are derived and who owns/publish the data is often ignored.…”

“…This [3]. The PROV specification provides the concepts and supporting definitions to enable the inter-operable interchange of provenance information in heterogeneous environments such as the Web [4]. This conforms to the principles of Linked Open Data (LOD), which encourages a set of best practices for publishing and connecting structured data on the Web [5].…”