Extracting Information from Twitter Screenshots

Screenshots are prevalent on social media as a common approach for information sharing. Users rarely verify before sharing a screenshot whether the post it contains is fake or real. Information sharing through fake screenshots can be highly responsible for misinformation and disinformation spread on social media. Our ultimate goal is to develop a tool that could take a screenshot of a tweet and provide a probability that the tweet is real, using resources found on the live web and in web archives. This paper provides methods for extracting the tweet text, timestamp, and Twitter handle from a screenshot of a tweet.

Making Changes in Webpages Discoverable: A Change-Text Search Interface for Web Archives

Webpages change over time, and web archives hold copies of historical versions of webpages. Users of web archives, such as journalists, want to find and view changes on webpages over time. However, the current search interfaces for web archives do not support this task. For the web archives that include a full-text search feature, multiple versions of the same webpage that match the search query are shown individually without enumerating changes, or are grouped together in a way that hides changes. We present a change text search engine that allows users to find changes in webpages. We describe the implementation of the search engine backend and frontend, including a tool that allows users to view the changes between two webpage versions in context as an animation. We evaluate the search engine with U.S. federal environmental webpages that changed between 2016 and 2020. The change text search results page can clearly show when terms and phrases were added or removed from webpages. The inverted index can also be queried to identify salient and frequently deleted terms in a corpus.

Profiling Web Archival Voids for Memento Routing

Prior work on web archive profiling were focused on Archival Holdings to describe what is present in an archive. This work defines and explores Archival Voids to establish a means to represent portions of URI spaces that are not present in a web archive. Archival Holdings and Archival Voids profiles can work independently or as complements to each other to maximize the Accuracy of Memento Aggregators. We discuss various sources of truth that can be used to create Archival Voids profiles. We use access logs from Arquivo.pt to create various Archival Voids profiles and analyze them against our MemGator access logs for evaluation. We find that we could have avoided more than 8% of additional False Positives on top of the 60% Accuracy we got from profiling Archival Holdings in our prior work, if Arquivo.pt were to provide an Archival Voids profile based on URIs that were requested hundreds of times and never returned any success responses.

365 Dots in 2019: Quantifying Attention of News Sources

We investigate the overlap of topics of online news articles from a variety of sources. To do this, we provide a platform for studying the news by measuring this overlap and scoring news stories according to the degree of attention in near-real time. This can enable multiple studies, including identifying topics that receive the most attention from news organizations and identifying slow news days versus major news days. Our application, StoryGraph, periodically (10-minute intervals) extracts the first five news articles from the RSS feeds of 17 US news media organizations across the partisanship spectrum (left, center, and right). From these articles, StoryGraph extracts named entities (PEOPLE, LOCATIONS, ORGANIZATIONS, etc.) and then represents each news article with its set of extracted named entities. Finally, StoryGraph generates a news similarity graph where the nodes represent news articles, and an edge between a pair of nodes represents a high degree of similarity between the nodes (similar news stories). Each news story within the news similarity graph is assigned an attention score which quantifies the amount of attention the topics in the news story receive collectively from the news media organizations. The StoryGraph service has been running since August 2017, and using this method, we determined that the top news story of 2018 was the "Kavanaugh hearings" with attention score of 25.85 on September 27, 2018. Similarly, the top news story for 2019 so far (2019-12-12) is "AG William Barr's release of his principal conclusions of the Mueller Report," with an attention score of 22.93 on March 24, 2019.