A Topic Recommender for Journalists

The way in which people acquire information on events and form their own opinion on them has changed dramatically with the advent of social media. For many readers, the news gathered from online sources become an opportunity to share points of view and information within micro-blogging platforms such as Twitter, mainly aimed at satisfying their communication needs. Furthermore, the need to deepen the aspects related to news stimulates a demand for additional information which is often met through online encyclopedias, such as Wikipedia. This behaviour has also influenced the way in which journalists write their articles, requiring a careful assessment of what actually interests the readers. The goal of this paper is to present a recommender system, What to Write and Why, capable of suggesting to a journalist, for a given event, the aspects still uncovered in news articles on which the readers focus their interest. The basic idea is to characterize an event according to the echo it receives in online news sources and associate it with the corresponding readers’ communicative and informative patterns, detected through the analysis of Twitter and Wikipedia, respectively. Our methodology temporally aligns the results of this analysis and recommends the concepts that emerge as topics of interest from Twitter and Wikipedia, either not covered or poorly covered in the published news articles

Summarization from Medical Documents: A Survey

Objective: The aim of this paper is to survey the recent work in medical documents summarization. Background: During the last decade, documents summarization got increasing attention by the AI research community. More recently it also attracted the interest of the medical research community as well, due to the enormous growth of information that is available to the physicians and researchers in medicine, through the large and growing number of published journals, conference proceedings, medical sites and portals on the World Wide Web, electronic medical records, etc. Methodology: This survey gives first a general background on documents summarization, presenting the factors that summarization depends upon, discussing evaluation issues and describing briefly the various types of summarization techniques. It then examines the characteristics of the medical domain through the different types of medical documents. Finally, it presents and discusses the summarization techniques used so far in the medical domain, referring to the corresponding systems and their characteristics. Discussion and conclusions: The paper discusses thoroughly the promising paths for future research in medical documents summarization. It mainly focuses on the issue of scaling to large collections of documents in various languages and from different media, on personalization issues, on portability to new sub-domains, and on the integration of summarization technology in practical applicationsComment: 21 pages, 4 table

Highlighting School of Education successes to build community

Master's Project (M.Ed.) University of Alaska Fairbanks, 2016The project is a WordPress site to showcase faculty and students. This site is a companion piece to the redesigned University of Alaska Fairbanks School of Education website. It is intended to provide a visual resource to be used by faculty and staff to promote the uniqueness of current and recent developments in the School o f Education. The site should serve as a space where staff and faculty may promote opportunities for current and recent graduates. It will also include graduate students’ experiences via research, projects, career stories and testimonials provided by students. These materials will be linked in from the School of Education website under the proposed title of Showcase

Video Timeline Modeling For News Story Understanding

In this paper, we present a novel problem, namely video timeline modeling. Our objective is to create a video-associated timeline from a set of videos related to a specific topic, thereby facilitating the content and structure understanding of the story being told. This problem has significant potential in various real-world applications, such as news story summarization. To bootstrap research in this area, we curate a realistic benchmark dataset, YouTube-News-Timeline, consisting of over $12$k timelines and $300$k YouTube news videos. Additionally, we propose a set of quantitative metrics as the protocol to comprehensively evaluate and compare methodologies. With such a testbed, we further develop and benchmark exploratory deep learning approaches to tackle this problem. We anticipate that this exploratory work will pave the way for further research in video timeline modeling. The assets are available via https://github.com/google-research/google-research/tree/master/video_timeline_modeling.Comment: Accepted as a spotlight by NeurIPS 2023, Track on Datasets and Benchmark

Storylines for practice: a visual storytelling approach to strengthen the science‑practice interface

A growing number of scientifc publications is available to promote sustainable river management. However, these publications target researchers rather than water management professionals who are responsible for the implementation of management practices. To bridge this science-to-practice gap, we conceptualize and propose a series of steps to prepare efective storylines targeted at a practitioner audience. We developed this approach within a research program that supports integrated and collaborative river management. We prepared three storylines, each based on one scientifc publication. The storylines combined text and interactive visuals using the ESRI StoryMaps tool to make them available online. Via focus groups with 44 participants from research and practice, we evaluated the perceived usefulness of and engagement with the content and design. We collected feedback from participants using a survey as well as via audio and screen recordings. Our fndings show that we should narrow down the audience of the storylines by tailoring them to the needs of project managers rather than specialized advisors. Therefore, the content should ofer more than a visual summary of the research by showing examples of the management application. A more engaging sequence with a clear protagonist is further required to better relate to the problem and the potential application. Although visuals and interactive elements were considered attractive, a multi-disciplinary editorial team is necessary to better complement the visuals’ design to the text. The level of detail of participants’ feedback shows that involving project managers to co-create storylines can be an important step for improvement.Peer reviewe

The Emerging Reality of Social Media: Erosion of Individual Privacy Through Cyber-vetting and Law’s Inability to Catch Up, 12 J. Marshall Rev. Intell. Prop. L. 551 (2013)

The rise of social media means that data about a large number of people is available in public and quasi-public digital locations. Employers, keen on taking advantage of this additional data to decrease the risk associated with an offer of employment, are engaging in “cyber-vetting”—non-consenting social media searches conducted by third parties or the employers themselves. To the extent that current law applies to this practice, the regulation it provides is weak and attacks only part of the problem. Left unchecked, cyber-vetting has the potential to fundamentally alter the scope of prospective employees’ rights. This article surveys the legal and practical implications of cyber-vetting and suggests broad reforms focused on intelligently balancing individual rights and legitimate employer interests