Story Point Estimation Using Issue Reports With Deep Attention Neural Network

Background: Estimating the effort required for software engineering tasks is incredibly tricky, but it is critical for project planning. Issue reports are frequently used in the agile community to describe tasks, and story points are used to estimate task effort. Aim: This paper proposes a machine learning regression model for estimating the number of story points needed to solve a task. The system can be trained from raw input data to predict outcomes without the need for manual feature engineering. Method: Hierarchical attention networks are used in the proposed model. It has two levels of attention mechanisms implemented at word and sentence levels. The model gradually constructs a document vector by grouping significant words into sentence vectors and then merging significant sentence vectors to create document vectors. Then, the document vectors are fed into a shallow neural network to predict the story point. Results: The experiments show that the proposed approach outperforms the state-of-the-art technique Deep-S which uses Recurrent Highway Networks. The proposed model has improved Mean Absolute Error (MAE) by an average of 16.6% and has improved Median Absolute Error (MdAE) by an average of 53%. Conclusion: An empirical evaluation shows that the proposed approach outperforms the previous work

Persuading the enemy: estimating the persuasive effects of partisan media with the preference-incorporating choice and assignment design

Does media choice cause polarization, or merely reflect it? We investigate a critical aspect of this puzzle: how partisan media contribute to attitude polarization among different groups of media consumers. We implement a new experimental design, called the Preference-Incorporating Choice and Assignment (PICA) design, that incorporates both free choice and forced exposure. We estimate jointly the degree of polarization caused by selective exposure and the persuasive effect of partisan media. Our design also enables us to conduct sensitivity analyses accounting for discrepancies between stated preferences and actual choice, a potential source of bias ignored in previous studies using similar designs. We find that partisan media can polarize both its regular consumers and inadvertent audiences who would otherwise not consume it, but ideologically-opposing media potentially also can ameliorate existing polarization between consumers. Taken together, these results deepen our understanding of when and how media polarize individuals.Accepted manuscrip

Media Coverage of EPA\u27s Draft Dioxin Reassessment Report

Using content analysis, the authors examine the utility of news media in democratic decision making

Fact or Fiction: What Do We Really Know About Human Trafficking?

Statistics form the core of many policies, funding decisions and program designs around human trafficking into forced labor and debt bondage. But are the statistics accurate? How can people decide whether statements such as the following ones are supported by evidence?This Issue Paper looks at several instances in which unreliable claims such as these have driven actions and policies. It evaluates some research, statements and statistics presented by the media, government officials, the UN and other international institutions, non-governmental organizations (NGOs) and experts. It goes behind the headlines and raises questions about the actual scope and nature of the problem of human trafficking, as well as the need for reliable evidence. While it may seem irrelevant to spend time "bean counting" when so many people are facing human rights abuses, it is necessary to know the nature and extent of the problem before designing effective laws and programs

Extraction and Analysis of Dynamic Conversational Networks from TV Series

Identifying and characterizing the dynamics of modern tv series subplots is an open problem. One way is to study the underlying social network of interactions between the characters. Standard dynamic network extraction methods rely on temporal integration, either over the whole considered period, or as a sequence of several time-slices. However, they turn out to be inappropriate in the case of tv series, because the scenes shown onscreen alternatively focus on parallel storylines, and do not necessarily respect a traditional chronology. In this article, we introduce Narrative Smoothing, a novel network extraction method taking advantage of the plot properties to solve some of their limitations. We apply our method to a corpus of 3 popular series, and compare it to both standard approaches. Narrative smoothing leads to more relevant observations when it comes to the characterization of the protagonists and their relationships, confirming its appropriateness to model the intertwined storylines constituting the plots.Comment: arXiv admin note: substantial text overlap with arXiv:1602.0781

Procrastination in the Workplace: Evidence from the U.S. Patent Office

Despite much theoretical attention to the concept of procrastination and much exploration of this phenomenon in laboratory settings, there remain few empirical investigations into the practice of procrastination in real world contexts, especially in the workplace. In this paper, we attempt to fill these gaps by exploring procrastination among U.S. patent examiners. We find that nearly half of examiners’ first substantive reports are completed immediately prior to the operable deadlines. Moreover, we find a range of additional empirical markers to support that this “end-loading” of reviews results from a model of procrastination rather than various alternative time-consistent models of behavior. In one such approach, we take advantage of the natural experiment afforded by the Patent Office’s staggered implementation of its telecommuting program, a large-scale development that we theorize might exacerbate employee self-control problems due to the ensuing reduction in direct supervision. Supporting the procrastination theory, we estimate an immediate spike in application end-loading and other indicia of procrastination upon the onset of telecommuting. Finally, contributing to a growing empirical literature over the efficiency of the patent examination process, we assess the consequences of procrastination for the quality of the reviews completed by the affected examiners. This analysis suggests that the primary harm stemming from procrastination is delay in the ultimate application process, with rushed reviews completed at deadlines resulting in the need for revisions in subsequent rounds of review. Our findings imply that nearly 1/6 of the annual growth in the Agency’s much-publicized backlog may be attributable to examiner procrastination

Downs, Stokes and the Dynamics of Electoral Choice

A six-wave 2005–09 national panel survey conducted in conjunction with the British Election Study provided data for an investigation of sources of stability and change in voters’ party preferences. The authors test competing spatial and valence theories of party choice and investigate the hypothesis that spatial calculations provide cues for making valence judgements. Analyses reveal that valence mechanisms – heuristics based on party leader images, party performance evaluations and mutable partisan attachments – outperform a spatial model in terms of strength of direct effects on party choice. However, spatial effects still have sizeable indirect effects on the vote via their influence on valence judgements. The results of exogeneity tests bolster claims about the flow of influence from spatial calculations to valence judgments to electoral choice.</jats:p

Assessing village food needs following a natural disaster in Papua New Guinea

Papua New Guinea is vulnerable to natural disasters, including drought and frost associated with El Niño weather events and excessive rainfall associated with La Niña events. Drought, frost and excessive rainfall can cause major disruptions to village food supplies. Drought also reduces villagers’ access to clean drinking water, which in turn has a negative impact on peoples’ health and the capacity of schools and hospitals to operate. There are often other impacts — damage to crops and property by wildfires, out-migration and an increased death rate. In 1997–98, and again in 2015–16, a major El Niño event caused significant disruption to drinking water and food supply for many Papua New Guinean villagers. Staff of many agencies, including those working through the Church Partnership Program El Niño Drought Response Program, were involved in assessing the impact and providing relief in 2015–16. This publication brings together the experiences of those working on the Church Partnership Program response to the 2015–16 El Niño event and serves as a guide for assessing future food shortages and to help those in need.Australian Government Department of Foreign Affairs and Trade (DFAT