A new metaphor of two-dimensional text for data-driven semantic modeling natural language is proposed, which provides an entirely angle on the representation text: not only syntagmatic relations are annotated in text, but also paradigmatic made explicit by generating lexical expansions. We operationalize distributional similarity a general framework large corpora, and describe method to generate similar terms context. Our evaluation shows that able produce highquality resources unsupervised...

An estimated 100,000 people work today as commercial content moderators. These moderators are often exposed to disturbing content, which can lead lasting psychological and emotional distress. This literature review investigates moderators' symptomatology, drawing on other occupations involving trauma exposure further guide understanding of both symptoms support mechanisms. We then introduce wellness interventions programmatic technological approaches improving wellness. Additionally, we...

Influencers are omnipresent on social media platforms. They occupy important digital real estate across a range of topical domains including beauty, fashion, and gaming. While researchers have contributed work the respective role that authenticity plays for influencers’ success described burgeoning industry within larger domain entertainment, comparably little is known about what happens when influencers get involved in politics, they harness their clout to promote political causes issues,...

The popular encrypted messaging and chat app WhatsApp played a key role in the election of Brazilian President Jair Bolsonaro 2018. present study builds on this knowledge showcases how continued to be used governmental operation spreading false misleading information popularly known Brazil as Office Hatred (OOH). By harnessing in-depth expert interviews with documentarians office’s daily operations—researchers, journalists, fact-checkers ( N = 10)—this draws up chronology OOH. Via...

Sunny Mitra, Ritwik Martin Riedl, Chris Biemann, Animesh Mukherjee, Pawan Goyal. Proceedings of the 52nd Annual Meeting Association for Computational Linguistics (Volume 1: Long Papers). 2014.

Abstract In this paper, we propose an unsupervised and automated method to identify noun sense changes based on rigorous analysis of time-varying text data available in the form millions digitized books tweets posted per day. We construct distributional-thesauri-based networks from at different time points cluster each them separately obtain word-centric clusters corresponding points. Subsequently, a split/join approach compare two find if there is ‘birth’ new sense. The also helps us older...

This article presents a general method to use information retrieved from the Latent Dirichlet Allocation (LDA) topic model for Text Segmentation: Using assignments instead of words in two well-known Segmentation algorithms, namely TextTiling and C99, leads significant improvements.Further, we introduce our own algorithm called TopicTiling, which is simplified version (Hearst, 1997).In study, evaluate optimize parameters LDA TopicTiling.A further contribution improve segmentation accuracy...

The 2014 amyotrophic lateral sclerosis Ice Bucket Challenge (IBC) received unprecedented attention by both news media and social audiences. Using content analysis, this research examines how digital utilized different values emotional appeals to cover the IBC. In addition, work includes a secondary analysis that what coverage characteristics influenced audiences share on Facebook Twitter. Results reveal while celebrity participation human interest stories were more likely be covered, played...

This research investigates how personality strength, news engagement, and consumption influence engagement on Reddit, an environment that affords varying degrees of anonymity is known to paradoxically host toxic supportive communities. Using a survey Redditors, findings suggest women are less likely comment post but equally vote read posts as men, indicating there may be hesitation engage in using more active participatory options within the site. Older users when compared younger users.

Heloisa Sturm Wilkersona* , Martin J. Riedlbc & Kelsey N. Whippled a Department of Communication, Purdue University Fort Wayne, IN, USAb School Journalism and Media, The Texas at Austin, TX, USAc Digital Media Research Program, USAd Department, Massachusetts, Amherst, MA, USA

This study examines support for regulation of and by platforms provides insights into public perceptions platform governance. While much the discourse surrounding evolves at a policy level between think tanks, journalists, academics political actors, little attention is paid to how people about platforms. Through representative survey US internet users (N = 1,022), we explore antecedents social media content moderation platforms, as well government. We connect these findings presumed effects...

This special issue explores connective democracy, a new theoretical approach to fighting and understanding political polarization divisiveness online. Connective democracy asks scholars think about solutions that bridge societal divides, particularly on social media. Our collection of six articles theorizes applies the concept global situations, such as nurturing freedom speech in Myanmar (Burma) discussions constitution Chile. The this also consider how is useful for current problems...

Chat apps such as WhatsApp, Telegram, and Signal are increasingly popular platforms for communication. Their sometimes-closed nature encryption affordances present researchers, governments, law enforcement with unique problems of access, traceability, and, ultimately, understanding. It also makes them useful vectors sowing disinformation. This research assumes a multi-platform perspective, describing the particularities how chat can be used toward disseminating mis- disinformation by way...

We ask how to practically build a model for German named entity recognition (NER) that performs at the state of art both contemporary and historical texts, i.e., big-data small-data scenario. The two best-performing families are pitted against each other (linear-chain CRFs BiLSTM) observe trade-off between expressiveness data requirements. BiLSTM outperforms CRF when large datasets available inferior smallest dataset. BiLSTMs profit substantially from transfer learning, which enables them be...

Complex Word Identification (CWI) is an important task in lexical simplification and text accessibility.Due to the lack of CWI datasets, previous works largely depend on Simple English Wikipedia edit histories for obtaining 'gold standard' annotations, which are mixed quality, limited only.We collect complex words/phrases (CP) English, German Spanish, annotated by both native non-native speakers, propose language independent features that can be used train multilingual crosslingual models.We...

Mass spectrometry (MS) offers a wide range of possibilities for analyzing biological samples containing complex mixtures proteins and peptides, by generating proteome profiles. The aim most profiling experiments is identification changes in protein patterns that are related to certain disease or clinical status might therefore be used improve diagnosis, staging, monitoring (1). Reproducibility spectra generated matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS crucial...

Among the central challenges of Ambient Assisted Living systems are autonomous and reliable recognition assisted person's current situation proactive offering rendering adequate assistance services. In context emergency support, such situations may be acute

In this paper we present a word decompounding method that is based on distributional semantics.Our does not require any linguistic knowledge and initialized using large monolingual corpus.The core idea of our approach parts compounds (like "candle" "stick") are semantically similar to the entire compound, which helps exclude spurious splits "candles" "tick").We report results for German Dutch: For German, unsupervised comes par with performance rule-based supervised significantly outperforms...

Though detection systems have been developed to identify obscene content such as pornography and violence, artificial intelligence is simply not good enough fully automate this task yet. Due the need for manual verification, social media companies may hire internal reviewers, contract specialized workers from third parties, or outsource online labor markets purpose of commercial moderation. These moderators are often exposed extreme suffer lasting psychological emotional damage. In work, we...

Abstract Online comment sections on news organizations' social media pages provide a unique forum for exploring attitudes toward platform governance and freedom of expression at the crossroads between people, platforms, providers. Amid ample political policy interest, little empirical evidence exists user perceptions governance. Through survey studies in Germany ( n = 1155) United States 1164), we comparative perspective responsibility attributions different regulatory actors who may...