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Hits 1 – 20 of 27

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Homepage2Vec: Language-Agnostic Website Embedding and Classification ...
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2
Better than Average: Paired Evaluation of NLP systems ...
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3
Classifying Dyads for Militarized Conflict Analysis ...
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4
Classifying Dyads for Militarized Conflict Analysis
In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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5
Cognitive Network Topology and Optimization of the Mental Lexicon ...
Burlacu, Adrian; West, Robert. - : Unpublished, 2021
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6
Linguistic effects on news headline success: Evidence from thousands of online field experiments (Registered Report Protocol)
In: PLoS One (2021)
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7
On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation ...
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8
On the limitations of cross-lingual encoders as exposed by reference-free machine translation evaluation
Zhao, Wei; Glavaš, Goran; Peyrard, Maxime. - : Association for Computational Linguistics, 2020
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9
Robust Cross-lingual Embeddings from Parallel Sentences ...
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10
Crosslingual Document Embedding as Reduced-Rank Ridge Regression ...
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11
Why the World Reads Wikipedia ...
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12
Why the World Reads Wikipedia ...
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13
Why the World Reads Wikipedia ...
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14
Causal Effects of Brevity on Style and Success in Social Media ...
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15
Message Distortion in Information Cascades
In: http://infoscience.epfl.ch/record/270657 (2019)
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16
Message Distortion in Information Cascades ...
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17
Reverse-Engineering Satire, or "Paper on Computational Humor Accepted despite Making Serious Advances"
In: http://infoscience.epfl.ch/record/271147 (2019)
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18
Why the World Reads Wikipedia: Beyond English Speakers
In: http://infoscience.epfl.ch/record/270302 (2019)
Abstract: As one of the Web's primary multilingual knowledge sources, Wikipedia is read by millions of people across the globe every day. Despite this global readership, little is known about why users read Wikipedia's various language editions. To bridge this gap, we conduct a comparative study by combining a large-scale survey of Wikipedia readers across 14 language editions with a log-based analysis of user activity. We proceed in three steps. First, we analyze the survey results to compare the prevalence of Wikipedia use cases across languages, discovering commonalities, but also substantial differences, among Wikipedia languages with respect to their usage. Second, we match survey responses to the respondents' traces in Wikipedia's server logs to characterize behavioral patterns associated with specific use cases, finding that distinctive patterns consistently mark certain use cases across language editions. Third, we show that certain Wikipedia use cases are more common in countries with certain socio-economic characteristics; e.g., in-depth reading of Wikipedia articles is substantially more common in countries with a low Human Development Index. These findings advance our understanding of reader motivations and behaviors across Wikipedia languages and have implications for Wikipedia editors and developers of Wikipedia and other Web technologies.
URL: http://infoscience.epfl.ch/record/270302/files/Final_Version.pdf
http://infoscience.epfl.ch/record/270302
https://doi.org/10.1145/3289600.3291021
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19
Crosslingual Document Embedding as Reduced-Rank Ridge Regression
In: http://infoscience.epfl.ch/record/263893 (2019)
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20
Churn Intent Detection in Multilingual Chatbot Conversations and Social Media ...
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