Event-based media monitoring methodology for Human Rights Watch

Executive Summary This report, prepared by a team of researchers from the University of Minnesota for Human Rights Watch (HRW), investigates the use of event-based media monitoring (EMM) to review its application, identify its strengths and weaknesses, and offer suggestions on how HRW can better utilize EMM in its own work. Media monitoring systems include both human-operated (manual) and automated systems, both of which we review throughout the report. The process begins with the selection of news sources, proceeds to the development of a coding manual (for manual searches) or “dictionary” (for automated searches), continues with gathering data, and concludes with the coding of news stories. EMM enables the near real-time tracking of events reported by the media, allowing researchers to get a sense of the scope of and trends in an event, but there are limits to what EMM can accomplish on its own. The media will only cover a portion of a given event, so information will always be missing from EMM data. EMM also introduces research biases of various kinds; mitigating these biases requires careful selection of media sources and clearly defined coding manuals or dictionaries. In manual EMM, coding the gathered data requires human researchers to apply codebook rules in order to collect consistent data from each story they read. In automated EMM, computers apply the dictionary directly to the news stories, automatically picking up the desired information. There are trade-offs in each system. Automated EMM can code stories far more quickly, but the software may incorrectly code stories, requiring manual corrections. Conversely, manual EMM allows for a more nuanced analysis, but the investment of time and effort may diminish the tool’s utility. We believe that both manual and automated EMM, when deployed correctly, can effectively support human rights research and advocacy

The Pig Story (Tiboi Sakkoko) Storytelling of Kinship, Memories of the Past, and Rights to Plots of Ancestral Land in Mentawai

This paper examines some significant elements of the pig story (tiboi sakkoko). This tale contains crucial information about the collective identity, ancestors and historical events affecting particular Mentawai kin-groups. As families do not preserve their culture and traditions in written form, storytellers of kin-groups have narrated the pig story from generation to generation so as to preserve it carefully. In the course of time, storytellers establish particular ways of telling their stories so as to remember the content and plot of the stories easily. Through the pig story, members of kin groups also recollect their ancestral place of origin and plots of ancestral lands. The role of human memory is indispensable to recalling all these important elements. Therefore, this paper analyses memories of the past of different family generations. To achieve its aims, this paper also evaluates the roles of family stories in the culture and traditions of Mentawai society

Endangered oral literature genres in Punan Tubu (East Kalimantan)

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Value-adding and value-extracting entrepreneurship at the margins

Empirical data is reported from two case studies on the methods used to establish and grow the businesses of two entrepreneurs operating in very different environments: one legitimate, the other illegitimate. Both utilize strong social skills to legitimize their behaviours but neither can be considered as mainstream or conventional entrepreneurial actors. The findings suggest that, despite the very different outcomes associated with their actions, both entrepreneurs exhibit similar enterprising skills and managerial capabilities as found in entrepreneurs engaged in non-marginal activities

Multimedia search without visual analysis: the value of linguistic and contextual information

This paper addresses the focus of this special issue by analyzing the potential contribution of linguistic content and other non-image aspects to the processing of audiovisual data. It summarizes the various ways in which linguistic content analysis contributes to enhancing the semantic annotation of multimedia content, and, as a consequence, to improving the effectiveness of conceptual media access tools. A number of techniques are presented, including the time-alignment of textual resources, audio and speech processing, content reduction and reasoning tools, and the exploitation of surface features

Global Health in Lights: Hollywood's Master Storytellers & Stars Highlight Global Health in Entertainment

Sandra de Castro Buffington, director of the Norman Lear Center's Hollywood, Health & Society program, moderated this discussion which brought top TV producers, writers and performers together with key Washington policymakers to focus on how global health is portrayed in entertainment media

Towards Building a Knowledge Base of Monetary Transactions from a News Collection

We address the problem of extracting structured representations of economic events from a large corpus of news articles, using a combination of natural language processing and machine learning techniques. The developed techniques allow for semi-automatic population of a financial knowledge base, which, in turn, may be used to support a range of data mining and exploration tasks. The key challenge we face in this domain is that the same event is often reported multiple times, with varying correctness of details. We address this challenge by first collecting all information pertinent to a given event from the entire corpus, then considering all possible representations of the event, and finally, using a supervised learning method, to rank these representations by the associated confidence scores. A main innovative element of our approach is that it jointly extracts and stores all attributes of the event as a single representation (quintuple). Using a purpose-built test set we demonstrate that our supervised learning approach can achieve 25% improvement in F1-score over baseline methods that consider the earliest, the latest or the most frequent reporting of the event.Comment: Proceedings of the 17th ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL '17), 201

Template Mining for Information Extraction from Digital Documents

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