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Using word embeddings for immigrant and refugee stereotype quantification in a diachronic and multilingual setting
Word embeddings are efficient machine-learning-based representations of human language used in many Natural Language Processing tasks nowadays. Due...
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Aksumite Settlement Patterns: Site Size Hierarchies and Spatial Clustering
Settlement pattern analysis offers a range of insights about social, economic, and political relationships of Aksumite civilization. Two common...
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Detection and context reconstruction of sub-events that influence the course of a news event from microblog discussions
Social media has become an inevitable part of human communication and the primary source for reading and tracking news events. Most news events...
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Content and interaction-based map** of Reddit posts related to information security
Ensuring the privacy and safety of platform users has become a complex objective due to the emerging threats that surround any type of network,...
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Exploring Gentrification Through Social Media Data and Text Clustering Techniques
Gentrification is a transformation of a working-class or an abandoned area of a city under the influence of redevelopment and influx of higher-income...
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Using Model-Based Clustering to Improve Qualitative Inquiry: Computer-Aided Qualitative Data Analysis, Latent Class Analysis, and Interpretive Transparency
A combination of computer-aided qualitative data analysis (CAQDAS) and latent class analysis (LCA) can substantially augment the qualitative analysis...
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Novel Approach and Innovative Strategy for Mall Customer Segmentation Using Machine Learning Techniques
Dividing up a company’s clientele into distinct groups is one of the most critical components of its decision-making support system. It is an...
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The protective effect of educational level varies as a function of the difficulty of the memory task in ageing
This study aimed to explore the effects of age and educational level on recall performance and organisational strategies used during recall as a...
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A bibliometric study on recent trends in artificial intelligence-based suspicious activity recognition
Recent years have seen a dramatic increase in the use of artificial intelligence (AI) in suspicious activity recognition (SAR). To better understand...
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Framing climate change in Nature and Science editorials: applications of supervised and unsupervised text categorization
Hulme et al. (Nat Clim Change, 8:515–521, 2018) manually coded ‘frames’ in 490 Nature and Science editorials (1966–2016) they found relevant for...
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High-frequency words have higher frequencies in Turkish social sciences article
Words, sentences, and paragraphs are the basis of texts. When we consider texts as data and want to establish a relationship between qualitative and...
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Applying unsupervised machine learning to counterterrorism
To advance the agenda in counterterrorism, this work demonstrates how analysts can combine unsupervised machine learning, exploratory data analysis,...
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Temporal communication dynamics in the aftermath of large-scale upheavals: do digital footprints reveal a stage model?
It has long been theorized that the exchange of information in the aftermath of large-scale upheavals ensues dynamics that follow a stage model,...
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Concept Mover’s Distance: measuring concept engagement via word embeddings in texts
We propose a method for measuring a text’s engagement with a focal concept using distributional representations of the meaning of words. More...
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Evolution of customer relationship management to data mining-based customer relationship management: a scientometric analysis
Scores of researchers have paid attention to empirical and conceptual dimensions of Customer relationship management (CRM). A few studies summarise...
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Development a Deeper Understanding of Visitors’ Sentiments Towards Natura 2000 Protected Areas: Evidence from Online Reviews
User-generated data shared by visitors on TripAdvisor provide opportunities to understand how people perceive the Natura 2000 protected areas during...
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Varieties of corona news: a cross-national study on the foundations of online misinformation production during the COVID-19 pandemic
Misinformation in the media is produced by hard-to-gauge thought mechanisms employed by individuals or collectivities. In this paper, we shed light...
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A deep learning framework for clickbait spoiler generation and type identification
Clickbait pertains to attention-grabbing or misleading content that sacrifices accuracy for clicks. This marketing tactic is widely used to drive...
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Using Word Embeddings to Analyze how Universities Conceptualize “Diversity” in their Online Institutional Presence
The term diversity can be operationalized demographically (in terms of physical or external characteristics such as race, gender, ethnicity and...
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Did the public attribute the Flint Water Crisis to racism as it was happening? Text analysis of Twitter data to examine causal attributions to racism during a public health crisis
The Flint Water Crisis (FWC) was an avoidable public health disaster that profoundly affected the city’s residents, a majority of whom are Black....
