Wiley

Bài viết này mô tả sự phát triển mới nhất của một cách tiếp cận tổng quát để phát hiện và hình dung các xu hướng nổi bật và các kiểu tạm thời trong văn học khoa học. Công trình này đóng góp đáng kể về lý thuyết và phương pháp luận cho việc hình dung các lĩnh vực tri thức tiến bộ. Một đặc điểm là chuyên ngành được khái niệm hóa và hình dung như một sự đối ngẫu theo thời gian giữa hai khái niệm cơ bản trong khoa học thông tin: các mặt trận nghiên cứu và nền tảng trí tuệ. Một mặt trận nghiên cứu được định nghĩa như một nhóm nổi bật và nhất thời của các khái niệm và các vấn đề nghiên cứu nền tảng. Nền tảng trí tuệ của một mặt trận nghiên cứu là dấu chân trích dẫn và đồng trích dẫn của nó trong văn học khoa học—một mạng lưới phát triển của các ấn phẩm khoa học được trích dẫn bởi các khái niệm mặt trận nghiên cứu. Thuật toán phát hiện bùng nổ của Kleinberg (2002) được điều chỉnh để nhận dạng các khái niệm mặt trận nghiên cứu nổi bật. Thước đo độ trung gian của Freeman (1979) được sử dụng để làm nổi bật các điểm chuyển đổi tiềm năng như các điểm chịu ảnh hưởng nền tảng trong thời gian. Hai quan điểm hình dung bổ sung được thiết kế và thực hiện: các quan điểm cụm và các quan điểm vùng thời gian. Những đóng góp của phương pháp là (a) bản chất của một nền tảng trí tuệ được nhận diện bằng thuật toán và theo thời gian bởi các thuật ngữ mặt trận nghiên cứu nổi bật, (b) giá trị của một cụm đồng trích dẫn được diễn giải rõ ràng theo các khái niệm mặt trận nghiên cứu, và (c) các điểm chịu ảnh hưởng nổi bật và được phát hiện bằng thuật toán giảm đáng kể độ phức tạp của một mạng lưới đã được hình dung. Quá trình mô hình hóa và hình dung được thực hiện trong CiteSpace II, một ứng dụng Java, và áp dụng vào phân tích hai lĩnh vực nghiên cứu: tuyệt chủng hàng loạt (1981–2004) và khủng bố (1990–2003). Các xu hướng nổi bật và các điểm chịu ảnh hưởng trong mạng lưới được hình dung đã được xác minh phối hợp với các chuyên gia trong lĩnh vực, là tác giả của các bài báo chịu ảnh hưởng. Các ngụ ý thực tiễn của công trình được thảo luận. Một số thách thức và cơ hội cho các nghiên cứu sau này được xác định.

Given a snapshot of a social network, can we infer which new interactions among its members are likely to occur in the near future? We formalize this question as the link‐prediction problem, and we develop approaches to link prediction based on measures for analyzing the “proximity” of nodes in a network. Experiments on large coauthorship networks suggest that information about future interactions can be extracted from network topology alone, and that fairly subtle measures for detecting node proximity can outperform more direct measures.

A huge number of informal messages are posted every day in social network sites, blogs, and discussion forums. Emotions seem to be frequently important in these texts for expressing friendship, showing social support or as part of online arguments. Algorithms to identify sentiment and sentiment strength are needed to help understand the role of emotion in this informal communication and also to identify inappropriate or anomalous affective utterances, potentially associated with threatening behavior to the self or others. Nevertheless, existing sentiment detection algorithms tend to be commercially oriented, designed to identify opinions about products rather than user behaviors. This article partly fills this gap with a new algorithm, SentiStrength, to extract sentiment strength from informal English text, using new methods to exploit the de facto grammars and spelling styles of cyberspace. Applied to MySpace comments and with a lookup table of term sentiment strengths optimized by machine learning, SentiStrength is able to predict positive emotion with 60.6% accuracy and negative emotion with 72.8% accuracy, both based upon strength scales of 1–5. The former, but not the latter, is better than baseline and a wide range of general machine learning approaches.

In the Web, making judgments of information quality and authority is a difficult task for most users because overall, there is no quality control mechanism. This study examines the problem of the judgment of information quality and cognitive authority by observing people's searching behavior in the Web. Its purpose is to understand the various factors that influence people's judgment of quality and authority in the Web, and the effects of those judgments on selection behaviors. Fifteen scholars from diverse disciplines participated, and data were collected combining verbal protocols during the searches, search logs, and postsearch interviews. It was found that the subjects made two distinct kinds of judgment: predictive judgment, and evaluative judgment. The factors influencing each judgment of quality and authority were identified in terms of characteristics of information objects, characteristics of sources, knowledge, situation, ranking in search output, and general assumption. Implications for Web design that will effectively support people's judgments of quality and authority are also discussed.

This article introduces the concept of relevance as viewed and applied in the context of IR evaluation, by presenting an overview of the multidimensional and dynamic nature of the concept. The literature on relevance reveals how the relevance concept, especially in regard to the multidimensionality of relevance, is many faceted, and does not just refer to the various relevance criteria users may apply in the process of judging relevance of retrieved information objects. From our point of view, the multidimensionality of relevance explains why some will argue that no consensus has been reached on the relevance concept. Thus, the objective of this article is to present an overview of the many different views and ways by which the concept of relevance is used—leading to a consistent and compatible understanding of the concept. In addition, special attention is paid to the type of situational relevance. Many researchers perceive situational relevance as the most realistic type of user relevance, and therefore situational relevance is discussed with reference to its potential dynamic nature, and as a requirement for interactive information retrieval (IIR) evaluation.

This paper revises David Ellis's information‐seeking behavior model of social scientists, which includes six generic features: starting, chaining, browsing, differentiating, monitoring, and extracting. The paper uses social science faculty researching stateless nations as the study population. The description and analysis of the information‐seeking behavior of this group of scholars is based on data collected through structured and semi‐structured electronic mail interviews. Sixty faculty members from 14 different countries were interviewed by e‐mail. For reality check purposes, face‐to‐face interviews with five faculty members were also conducted. Although the study confirmed Ellis's model, it found that a fuller description of the information‐seeking process of social scientists studying stateless nations should include four additional features besides those identified by Ellis. These new features are: accessing, networking, verifying, and information managing. In view of that, the study develops a new model, which, unlike Ellis's, groups all the features into four interrelated stages: searching, accessing, processing, and ending. This new model is fully described and its implications on research and practice are discussed. How and why scholars studied here are different than other academic social scientists is also discussed.

Teenagers are among the most prolific users of social network sites (SNS). Emerging studies find that youth spend a considerable portion of their daily life interacting through social media. Subsequently, questions and controversies emerge about the effects SNS have on adolescent development. This review outlines the theoretical frameworks researchers have used to understand adolescents and SNS. It brings together work from disparate fields that examine the relationship between SNS and social capital, privacy, youth safety, psychological well‐being, and educational achievement. These research strands speak to high‐profile concerns and controversies that surround youth participation in these online communities, and offer ripe areas for future research.

Despite the rapid growth in social network sites and in data mining for emotion (sentiment analysis), little research has tied the two together, and none has had social science goals. This article examines the extent to which emotion is present in MySpace comments, using a combination of data mining and content analysis, and exploring age and gender. A random sample of 819 public comments to or from U.S. users was manually classified for strength of positive and negative emotion. Two thirds of the comments expressed positive emotion, but a minority (20%) contained negative emotion, confirming that MySpace is an extraordinarily emotion‐rich environment. Females are likely to give and receive more positive comments than are males, but there is no difference for negative comments. It is thus possible that females are more successful social network site users partly because of their greater ability to textually harness positive affect.

How does publication pressure in modern‐day universities affect the intrinsic and extrinsic rewards in science? By using a worldwide survey among demographers in developed and developing countries, the authors show that the large majority perceive the publication pressure as high, but more so in Anglo‐Saxon countries and to a lesser extent in Western Europe. However, scholars see both the pros (upward mobility) and cons (excessive publication and uncitedness, neglect of policy issues, etc.) of the so‐called publish‐or‐perish culture. By measuring behavior in terms of reading and publishing, and perceived extrinsic rewards and stated intrinsic rewards of practicing science, it turns out that publication pressure negatively affects the orientation of demographers towards policy and knowledge sharing. There are no signs that the pressure affects reading and publishing outside the core discipline.

This study investigated Simon's behavioral decision‐making theories of bounded rationality and satisficing in relation to young people's decision making in the World Wide Web, and considered the role of personal preferences in Web‐based decisions. It employed a qualitative research methodology involving group interviews with 22 adolescent females. Data analysis took the form of iterative pattern coding using QSR NUD*IST Vivo qualitative data analysis software. Data analysis revealed that the study participants did operate within the limits of bounded rationality. These limits took the form of time constraints, information overload, and physical constraints. Data analysis also uncovered two major satisficing behaviors—reduction and termination. Personal preference was found to play a major role in Web site evaluation in the areas of graphic/multimedia and subject content preferences. This study has related implications for Web site designers and for adult intermediaries who work with young people and the Web.