Do you have a favourite YouTuber? Are you worried that you see too many native ads on Instagram? Are you following the latest events on Twitter? Do you have a passion for Natural Language Processing? Then we need to talk (keep reading)
Together with my colleague from law (Catalina Goanta) we are looking for a PhD candidate working on computational analysis methods for advertising language on social media. This is part of the ERC starting grant project on HUMANads, award to Catalina last year. We are looking for somebody with a background in Computer Science (or similar) with focus/interest on NLP. Feel free to reach out if you have more questions. Check the full ad below (or here<https://www.academictransfer.com/en/319811/phd-position-a-computational-analysis-of-advertising-language-on-social-media-10-fte/>), apply by December 1st via this link<https://www.uu.nl/en/organisation/working-at-utrecht-university/jobs/phd-position-a-computational-analysis-of-advertising-language-on-social-media-10-fte> Best, -Jerry PhD position 'A computational analysis of advertising language on social media' (1.0 FTE) JOB DESCRIPTION The Utrecht Centre for Regulation and Enforcement in Europe at the Utrecht School of Law, Faculty of Law, Economics and Governance, is looking for a PhD candidate to conduct research in natural legal language processing and social media advertising under the supervision of dr. Catalina Goanta (Utrecht University), and dr. Gerasimos (Jerry) Spanakis (Maastricht University). Content monetization reflects a new era of social media business models, changing the nature of digital advertising from platform to human ads. Human ads are Internet influencers (also referred to as content creators) who earn revenue from social media advertising by creating authentic, relatable advertising content for their armies of followers. While their activity has been touted as a new form of creative labour, the overlap between their freedom of expression, political thought and advertising interests raises some serious concerns. One underlying danger is the convergence of speech in two ways. Consumers and citizens can no longer distinguish (i) between ads and non-ads, and (ii) between commercial and political communications. This is a new form of consumer vulnerability on digital markets where speech cannot be separated from platform infrastructure. Human ads are an emerging category of stakeholders who turn engagement into currency in novel ways. Users are faced with a double transparency problem: (i) human ads have incentives to hide commercial interests, and (ii) platforms have incentives to algorithmically amplify human ads engagement in opaque ways. This reflects a general good faith and fair dealing problem: the social media economy is increasingly based on deceit. However, we know very little about the size of deceit on social media. Even basic questions such as defining influencers or understanding how much sponsored content they post are difficult to formalize and compute. This PhD project consists in conducting interdisciplinary research to develop methodologies for the classification and detection of advertising language on social media. The PhD project will be mainly focused on the application of natural language processing to regulatory issues arising out of the proliferation of commercial and political advertising on social media, but could potentially also include web measurement and social network analysis approaches. Examples of questions which could fall under the PhD project include: * What are the characteristics of commercial v political advertising language on social media? * What kind of research methodologies can be used to classify social media content that is monetized by content creators/influencers? * How can content creators/influencers be computationally defined? * How can we use computer science methodologies to identify, describe and measure social media harms arising out of the proliferation of hidden advertising? This PhD position is part of the European Research Council Starting Grant HUMANads. The PhD candidate will have an opportunity and be expected to further define the initial research objectives set out by the project, in collaboration with the supervision team. This PhD position will be part of a broader project team featuring computer scientists, law and media scholars, and it will be based in the RENFORCE research center and the Molengraaff Institute for private law<https://www.uu.nl/en/organisation/utrecht-university-school-of-law/about-the-school-of-law/departments>. requirements * Academic excellence proven through a good track record of initiatives related to, among others, academic research; * Obtained (or obtained by the start of the PhD trajectory) Master in Computer Science or a Master in adjacent fields such as Computational Social Sciences, Data Science or Empirical Legal Studies; * Interest in being part of an interdisciplinary team; * Interest in being the first computer science PhD candidate at Utrecht Law School; * Knowledge of natural language processing (and related programming frameworks); * Practical experience with programming (esp. Python); * Affinity to or interest in developing knowledge about social network analysis and web measurement; * Affinity to or interest in developing practical knowledge about social media technologies; * Demonstrable strong interest in doing scientific research and specifically research on the subject of the PhD project; * Ability to process and critically assess large body of complex information; * Clear, critical and creative thinking; * Good planning and organizing skills, ability to deliver high-quality results on time; * Ability to function both independently and under supervision, communicate to the supervisor and process feedback effectively; * Sense of initiative and proactive thinking; * Excellent writing skills; * Excellent command of English. CONDITIONS OF EMPLOYMENT This is an appointment of 1.0 FTE for the duration of 18 months. Upon a positive evaluation of the PhD student’s performance the contract will be extended by a further 2.5 years. The gross salary starts with €2,541 per month in the first year and increases to €3,247 per month in the fourth year of employment (scale P according to the Collective Employment Agreement of the Dutch Universities) for a full-time employment. Besides that, you will receive a holiday allowance of 8% and a year-end bonus of 8.3%. Utrecht University also has an appealing package of terms of employment<https://www.uu.nl/en/organisation/working-at-utrecht-university/terms-of-employment>, including the choice for a good balance between work and private (a good arrangement for leave, among other things), possibilities for development and an excellent pension scheme. For more information, please visit working at Utrecht University<https://www.uu.nl/en/organisation/working-at-utrecht-university> The starting date will be 1 March 2023. The interviews will be scheduled in December 2022. Gerasimos (Jerry) Spanakis, PhD Assistant Professor Department of Advanced Computing Sciences | Maastricht Law+Tech Lab Faculty of Science and Engineering [email protected]<mailto:[email protected]> https://dke.maastrichtuniversity.nl/jerry.spanakis/ [image001.png] https://www.twitter.com/gerasimoss Paul-Henri Spaaklaan 1, 6229EN, Maastricht, The Netherlands, Room C4.029A Postbus 616, 6200 MD Maastricht T 0031(0)4338-83916 [image002.jpg]
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