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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5 Hits 1 – 20 of 87 1 Parler comme jamais. La langue, ce qu'on croit et ce qu'on en sait Véron, Laélia; Candea, Maria. - : HAL CCSD, 2021. : Le Robert / Binge audio, 2021 In: https://hal.archives-ouvertes.fr/hal-03377078 ; Le Robert / Binge audio, 2021, 9782321016687 (2021) BASE Show details 2 The Challenges of Digital Diplomacy in the Era of Globalization: The Case of the United Arab Emirates Antwi-Boateng, Osman; Al Mazrouei, Khadija Ali Mohammed In: International Journal of Communication; Vol 15 (2021); 19 ; 1932-8036 (2021) BASE Show details 3 Exploiting BERT and RoBERTa to Improve Performance for Aspect Based Sentiment Analysis Narayanaswamy, Gagan Reddy. - : Technological University Dublin, 2021 In: Dissertations (2021) BASE Show details 4 Distinguishing fake and real news of twitter data with the help of machine learning techniques Shah, Aanan. - : Laurentian University of Sudbury, 2021 BASE Show details 5 Using language models for holistic language variety comparisons ... McNeill, Joshua. - : Open Science Framework, 2021 BASE Show details 6 Orthographic variation of (lol) on Twitter ... McNeill, Joshua. - : Open Science Framework, 2021 BASE Show details 7 Tweeting on dementia: A snapshot of the content and sentiment of tweets associated with dementia Robertshaw, David; Babicova, Ivana In: First Monday; Volume 26, Number 6 - 7 June 2021 ; 1396-0466 (2021) BASE Show details 8 Narrativised simile and emotional responses to Brexit Barbara Dancygier In: Russian Journal of Linguistics, Vol 25, Iss 3, Pp 663-684 (2021) (2021) BASE Show details 9 “You’re too thick to change the station” – Impoliteness, insults and responses to insults on Twitter Bączkowska Anna In: Topics in Linguistics, Vol 22, Iss 2, Pp 62-84 (2021) (2021) BASE Show details 10 Implicit vs explicit evaluation: How English-speaking Twitter users discuss migration problems Elena V. Gabrielova; Olga I. Maksimenko In: Russian Journal of Linguistics, Vol 25, Iss 1, Pp 105-124 (2021) (2021) Abstract: The current research answers the question how Twitter users express their evaluation of topical social problems (explicitly or implicitly) and what linguistic means they use, being restricted by the allowed length of the message. The article explores how Twitter users communicate with each other and exchange ideas on social issues of great importance, express their feelings using a number of linguistic means, while being limited by a fixed number of characters, and form solidarity, being geographically distant from each other. The research is focused on the linguistic tools employed by Twitter users in order to express their personal attitude. The subject chosen for study was the migration processes in Europe and the USA. The aim of the current investigation is to determine the correlation between the attitudes of English-speaking users towards migration and the way they are expressed implicitly or explicitly. The authors make an attempt to define which tools contribute to the implicit or explicit nature of the utterances. The material includes 100 tweets of English-speaking users collected from February 1 to July 31, 2017. The choice of the time period is defined by significant events in Trumps migration policy and their consequences. The research is based on the content analysis of the material carried out by means of the Atlas.ti program. The software performs the coding of textual units, counts the frequency of codes and their correlation. The results of the research show that Twitter users tend to express their critical attitudes towards migration, rather than approve of it or sympathise with migrants. Criticism is more often expressed implicitly rather than explicitly. In order to disguise the attitude and feelings, the English-speaking users of Twitter employed irony, questions and quotations, while the explicit expression of attitudes was done by means of imperative structures. It is also worth mentioning that ellipses, contractions and abbreviations were used quite frequently due to the word limit of tweets. At the same time, the lack of knowledge about extralinguistic factors and personal characteristics of users makes the process of interpretation of tweets rather challenging. The findings of the current research suggest the necessity to take into account implicit negative attitudes while carrying out the analysis of public opinion on Twitter. Keyword: explicit evaluation; implicit evaluation; linguistic tools; migration; online communication; P1-1091; Philology. Linguistics; twitter URL: https://doi.org/10.22363/2687-0088-2021-25-1-105-124 https://doaj.org/article/97ff8178edad4c50b1d387eb8cb91d7b BASE Hide details 11 eterna regularidad de los participios Miguel Silvestre Llamas In: Domínios de Lingu@gem, Vol 16, Iss 2, Pp 843-869 (2021) (2021) BASE Show details 12 Spanish politicians in Twitter: A linguistic analysis of their written discourse Ricardo Casañ Pitarch In: Ibérica, Vol 40, Iss 1, Pp 195-216 (2021) (2021) BASE Show details 13 Construcción de la imagen colectiva de grupos a favor del Acuerdo de paz de Colombia en Twitter / Construction of the collective image of groups in favor of the Colombian peace agreement on Twitter Laura Cristina Bonilla-Neira In: Revista de Estudos da Linguagem, Vol 29, Iss 4, Pp 2225-2257 (2021) (2021) BASE Show details 14 Monitoring Users’ Behavior: Anti-Immigration Speech Detection on Twitter Pitropakis, Nikolaos; Kokot, Kamil; Gkatzia, Dimitra. - : MDPI, 2020 BASE Show details 15 Independent Component Analysis for Trustworthy Cyberspace during High Impact Events: An Application to Covid-19 ... Boukouvalas, Zois; Mallinson, Christine; Crothers, Evan. - : Maryland Shared Open Access Repository, 2020 BASE Show details 16 Temporally-Informed Analysis of Named Entity Recognition ... Rijhwani, Shruti; Preoțiuc-Pietro, Daniel. - : Zenodo, 2020 BASE Show details 17 Temporally-Informed Analysis of Named Entity Recognition ... Rijhwani, Shruti; Preoțiuc-Pietro, Daniel. - : Zenodo, 2020 BASE Show details 18 Mapping the languages of Twitter in Finland: richness and diversity in space and time ... Hiippala, Tuomo; Väisänen, Tuomas; Toivonen, Tuuli. - : Zenodo, 2020 BASE Show details 19 Mapping the languages of Twitter in Finland: richness and diversity in space and time ... Hiippala, Tuomo; Väisänen, Tuomas; Toivonen, Tuuli. - : Zenodo, 2020 BASE Show details 20 A large-scale COVID-19 Twitter chatter dataset for open scientific research - an international collaboration ... Banda, Juan M.; Tekumalla, Ramya; Wang, Guanyu. - : Zenodo, 2020 BASE Show details Page: 1 2 3 4 5

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