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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 Hits 1 – 10 of 10 1 Can pre-trained Transformers be used in detecting complex sensitive sentences? -- A Monsanto case study ... Timmer, Roelien C.; Liebowitz, David; Nepal, Surya. - : arXiv, 2022 BASE Show details 2 TSM: Measuring the Enticement of Honeyfiles with Natural Language Processing Timmer, Roelien; Liebowitz, David; Nepal, Surya. - 2022 BASE Show details 3 The importance of social identity on password formulations [<Journal>] Grobler, Marthie [Verfasser]; Chamikara, M. A. P. [Verfasser]; Abbott, Jacob [Verfasser]. DNB Subject Category Language Show details 4 DAN: Dual-View Representation Learning for Adapting Stance Classifiers to New Domains ... Xu, Chang; Paris, Cecile; Nepal, Surya. - : arXiv, 2020 BASE Show details 5 Assessing Social License to Operate from the Public Discourse on Social Media ... The 28th International Conference on Computational Linguistics 2020; Nepal, Surya; Paris, Cecile; Sparks, Ross; VanderLinden, Keith; Xu, Chang. - : Underline Science Inc., 2020 Abstract: Organisations are monitoring their Social License to Operate (SLO) with increasing regularity.SLO, the level of support organisations gain from the public, is typically assessed through surveys or focus groups, which require expensive manual efforts and yield quickly-outdated results. In this paper, we present SIRTA (Social Insight via real-Time Text Analytics), a novel real-time text analytics system for assessing and monitoring organisations’ SLO levels by analysing the public discourse from social posts. To assess SLO levels, our insight is to extract and transform peoples’ stances towards an organisation into SLO levels. SIRTA achieves this by performing a chain of three text classification tasks, where it identifies task-relevant social posts, discovers keySLO risks discussed in the posts, and infers stances specific to the SLO risks. We leverage recent language understanding techniques (e.g., BERT) for building our classifiers. To monitor SLOlevels over time, SIRTA employs quality control mechanisms to ... Keyword: Computer and Information Science; Natural Language Processing; Neural Network URL: https://dx.doi.org/10.48448/pyfv-mh72 https://underline.io/lecture/6111-assessing-social-license-to-operate-from-the-public-discourse-on-social-media BASE Hide details 6 Recognising Agreement and Disagreement between Stances with Reason Comparing Networks ... Xu, Chang; Paris, Cecile; Nepal, Surya. - : arXiv, 2019 BASE Show details 7 Catering to your concerns: Automatic generation of personalised security-centric descriptions for Android apps Wu, Tingmin; Tang, Lihong; Zhang, Rongjunchen... In: ACM Transactions on Cyber-Physical Systems, Vol. 3, no. 4 (Sep 2019), article no. 36 (2019) BASE Show details 8 Cross-Target Stance Classification with Self-Attention Networks ... Xu, Chang; Paris, Cecile; Nepal, Surya. - : arXiv, 2018 BASE Show details 9 Catering to Your Concerns: Automatic Generation of Personalised Security-Centric Descriptions for Android Apps ... Wu, Tingmin; Tang, Lihong; Zhang, Rongjunchen. - : arXiv, 2018 BASE Show details 10 Incorporating tweet relationships into topic derivation Nugroho, Robertus; Molla-Aliod, Diego; Yang, Jian. - : Singapore : Springer, 2016 BASE Show details

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