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of 73
pro vyhledávání: '"Lawrence Birnbaum"'
Publikováno v:
CHI Extended Abstracts
We have developed a conversational recommendation system designed to help users navigate through a set of limited options to find the best choice. Unlike many internet scale systems that use a singular set of search terms and return a ranked list of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::df73d85d34222eb3083799aa52d7567f
Autor:
Victor S. Bursztyn, Lawrence Birnbaum
Publikováno v:
ASONAM
There is growing concern about the use of social platforms to push political narratives during elections. One very recent case is Brazil's, where WhatsApp is now widely perceived as a key enabler of the far-right's rise to power. In this paper, we pe
Autor:
Lawrence Birnbaum, Tanja Aitamurto, Jessica Hullman, Nicholas Diakopoulos, Matilda Hanson, Christopher Anderson, Mike Ananny, Nick Ritchie
Publikováno v:
CHI Extended Abstracts
While new media technologies hold the potential to serve journalism's dual goals of informing and engaging the public, these technologies also challenge the journalistic norms of accuracy, impartiality and transparency. The key question in this works
Autor:
Miriam Boon, Lawrence Birnbaum
Publikováno v:
IUI Companion
Modern election news reporting tends to focus on who is winning and on campaign strategies - what is often called "Horse Race" coverage. With the ultimate goals of better understanding the mix of election story types presented by different venues, he
Publikováno v:
IUI
News articles often use narrative frames to present people, organizations, and facts. These narrative frames follow cultural archetypes, enabling readers to associate each of the presented elements with familiar stereotypes, well-known characters, an
Publikováno v:
ACL (2)
Intelligent systems require common sense, but automatically extracting this knowledge from text can be difficult. We propose and assess methods for extracting one type of commonsense knowledge, object-property comparisons, from pre-trained embeddings
Publikováno v:
ASONAM
Whether it’s a social media system populating a news feed or a user searching for content to share, decisions are constantly being made on the basis of semantic information. Topic, sentiment, and preference are among the many semantic dimensions of
Publikováno v:
ASONAM
AttitudeBuzz is a system that analyzes and presents complex social attitudes based on geolocated social media data. The system uses a machine learning model to apply highly domain-specific sentiment analysis to such data, specifically Twitter, by lea
Publikováno v:
IUI Companion
We describe intelligent information technologies designed to automatically provide both journalists and ordinary newsreaders with a broad range of the contextual information they need in order to better understand news stories, presented in an immedi
Publikováno v:
Knowledge-Based Systems. 14:37-53
Our central claim is that user interactions with productivity applications (e.g. word processors, Web browsers, etc.) provide rich contextual information that can be leveraged to support just-in-time access to task-relevant information. As evidence f