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20132020
most citedWhy We Read Wikipedia

90 citations · 198 across the 8 of their papers we have counts for

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Showing 2019Show all

7 papers · 1 filter

cs.SI2019

Causal Effects of Brevity on Style and Success in Social Media

Kristina Gligoric, Ashton Anderson, Robert West

In online communities, where billions of people strive to propagate their messages, understanding how wording affects success is of primary importance. In this work, we are interes…

cs.CL201914 cited

Crosslingual Document Embedding as Reduced-Rank Ridge Regression

Martin Josifoski, Ivan S. Paskov, Hristo S. Paskov +2

There has recently been much interest in extending vector-based word representations to multiple languages, such that words can be compared across languages. In this paper, we shif…

cs.IR2019

Eliciting New Wikipedia Users' Interests via Automatically Mined Questionnaires: For a Warm Welcome, Not a Cold Start

Ramtin Yazdanian, Leila Zia, Jonathan Morgan +2

Every day, thousands of users sign up as new Wikipedia contributors. Once joined, these users have to decide which articles to contribute to, which users to seek out and learn from…

cs.SI20191 cited

Hot Streaks on Social Media

Kiran Garimella, Robert West

Measuring the impact and success of human performance is common in various disciplines, including art, science, and sports. Quantifying impact also plays a key role on social media…

cs.CL20191 cited

Expanding the Text Classification Toolbox with Cross-Lingual Embeddings

Meryem M'hamdi, Robert West, Andreea Hossmann +2

Most work in text classification and Natural Language Processing (NLP) focuses on English or a handful of other languages that have text corpora of hundreds of millions of words. T…

cs.SI201911 cited

Message Distortion in Information Cascades

Manoel Horta Ribeiro, Kristina Gligorić, Robert West

Information diffusion is usually modeled as a process in which immutable pieces of information propagate over a network. In reality, however, messages are not immutable, but may be…