‘Warren Buffet is my cousin’: shaping public understanding of big data biotechnology,direct-to-consumer genomics,and 23andMe on Twitter

Scholars, educators, regulators, pundits, and other observers are advocating for regulation and oversight of direct-to-consumer (DTC) genomic testing. As a result, the technology has been subject of highly visible public and regulatory controversy. In this article, we explore the nature and the shape of the sentiment of public discourse about the DTC company, 23andMe. We conduct a quantitative content analysis and qualitative framing analysis on Tweets. We find that the discourse surrounding DTC genomics and 23andMe is largely positive. We also identify a number of frames users deploy to debate, discuss, and share their experiences with DTC genomics and 23andMe. We argue that these frames create meaning around this emerging technology for its users.     

Do Mission Statements Matter for Nonprofit Performance?

In this exploratory study, we examine whether organizational mission statement attributes make a difference to the performance of nonprofit performing arts organizations. We use text analysis to measure two semantic attributes—activity and commonality—of mission statements. We examine whether these attributes are associated with improved performance for the instrumental and expressive functions of nonprofit performing arts organizations. Our findings indicate that the mission statement attribute activity is associated with improved performance for both instrumental and expressive functions. Our analysis of nonfindings for the mission statement attribute commonality suggests that there is a need to develop and use content analysis tools tailored to nonprofit contexts.     

Birds of a feather petition together? Characterizing e-petitioning through the lens of platform data

E-petitioning platforms are increasingly popular in Western democracies and considered by some lawmakers and scholars to enhance citizen participation in political decision-making. In addition to social media and other channels for informal political communication, online petitioning is regarded as both a useful instrument to afford citizens a more important role in the political process and allow them to express support for issues which they find relevant. Building on existing pre-internet systems, e-petitioning websites are increasingly implemented to make it easier and faster to set up and sign petitions. However, little attention has so far been given to the relationship between different styles of usage and the causes supported by different groups of users. The functional difference between signing paper-based petitions vs. doing so online is especially notable with regard to users who sign large numbers of petitions. To characterize this relationship, we examine the intensity of user participation in the German Bundestag’s online petitioning platform through the lens of platform data collected over a period of five years, and conduct an analysis of highly active users and their political preferences. We find that users who sign just a single petition favor different policy areas than those who sign many petitions on a variety of issues. We conclude our analysis with observations on the potential of behavioral data for assessing the dynamics of online participation, and suggest that quantity (the number of signed petitions) and quality (favored policy areas) need more systematic joint assessment.     

What is gained and what is left to be done when content analysis is added to network analysis in the study of a social movement: Twitter use during Gezi Park

As social movements relying on the weak ties found in social networks have spread around the world, researchers have taken several approaches to understanding how networks function in such instances as the Arab Spring. While social scientists have primarily relied on survey or content analysis methodology, network scientists have used social network analysis. This research combines content analysis with the automated techniques of network analysis to determine the roles played by those using Twitter to communicate during the Turkish Gezi Park uprising. Based on a network analysis of nearly 2.4 million tweets and a content analysis of a subset of 5126 of those tweets, we found that information sharing was by far the most common use of the tweets and retweets, while tweets that indicated leadership of the movement constituted a small percentage of the overall number of tweets. Using automated techniques, we experimented with coded variables from content analysis to compute the most discriminative tokens and to predict values for each variable using only textual information. We achieved 0.61 precision on identifying types of shared information. Our results on detecting the position of user in the protest and purpose of the tweets achieved 0.42 and 0.33 precision, respectively, illustrating the necessity of user cooperation and the shortcomings of automated techniques. Based on annotated values of user tweets, we computed similarities between users considering their information production and consumption. User similarities are used to compute clusters of individuals with similar behaviors, and we interpreted average activities for those groups.     

Managing Serials in an Institutional Repository: An Interview With Kay Teel

ABSTRACT

In this interview from March 2017, Kay Teel, metadata librarian for serials and arts resources at the Stanford University Libraries, discusses the issues involved in providing access to serials through an institutional repository.     

Influence of competition level on referees’ decision-making in handball

The influence of competition level on referees’ decision-making was investigated. Referees’ decisions in 90 handball games (30 games X 3 competition levels) were observed in different situations related to the advantage rule, and 100 referees from two different levels of expertise were subsequently asked to offer explanations for the competition-level effects from the first part of the study. Results revealed that at the highest level of competition referees intervened less frequently with sporting sanctions, but more frequently with disciplinary sanctions. These effects were apparent mainly in immediate intervention situations and unsuccessful advantage situations, but not in successful situations. Referees explained these effects of competition level in terms of a player competence stereotype, in addition to referees’ different expertise across competition level. The implications of the findings for understanding how status-related stereotypes impact on intervention behavior are discussed.     

旁观者心态与张爱玲小说的叙事策略

中国文学史对张爱玲一直有某些误解,其中之一就是张爱玲的“冷眼旁观”。她这种貌似清高的创作姿态,给很多读者留下了冷漠薄情的印象。事实上,张爱玲是个“外冷内热”的人,这也正是她的旁观者心态的本质。了解她的旁观者心态的表现与动因对于她的叙事策略研究有很大帮助,也有利于我们进一步了解她的创作在人性、历史、哲学等方面达到的深度。     

Vietnam’s economy: Achievements and perspective

In last several years, Vietnams economy has reached significant achievements. Those are clearly seen by analyzing economic growth, economic structure transformation, trade and investment and Vietnams economy competitiveness. However, in the process of development, Vietnams economy is still facing many difficulties and challenges. Vietnam is accelerating speed of innovation process, is active and quicker in international economic integration in order to complete the economic – social objectives in the period of 2001–2005 with annual average economic growth rate of 7.5%.     

融合内容分析和关联分析的短生命周期体验品需求特征模式挖掘方法研究

挖掘特定产品的需求模式无法从整体掌握该类产品的市场特征;短生命周期体验品因缺乏历史销售数据,并且销售总量波动性极大,尤其需要从整体掌握销售总量与产品属性间关系的需求特征规律,但又难以挖掘,亟待提出适用于该类产品的需求特征模式挖掘方法。基于按销售总量分区后各区的需求特征的规律性,提出了一种按销售总量分区、以已有产品介绍集和销售总量为源信息、适用于新产品开发前使用、融合内容分析和关联分析的短生命周期体验品需求特征模式挖掘方法。该方法包括基于内容分析法的产品属性挖掘方法和基于关联分析的产品属性关系模式挖掘方法。前者可以得到较全面的产品属性;后者能够构建不同销售总量区间内产品集的属性关系模式,得到各区间的产品属性关系网,获得高销售总量区间具备,但中、低区间不具备的属性关系模式,从而获得需求特征模式。通过不断更新产品介绍集和销售总量并迭代挖掘,该方法能够动态挖掘需求特征模式。最后利用2013至2016年国产犯罪和爱情类电影数据验证了该方法的可行性,并得到了这两类电影的产品属性及近年的需求特征模式,可用于指导这两类电影的创作。