As HCI is applied in increasingly diverse contexts, it is important to consider situations in which computational or information technologies may be less appropriate. This paper presents a series of questions that can help researchers, designers, and practitioners articulate a technology's appropriateness or inappropriateness. Use of these questions is demonstrated via examples from the literature. The paper concludes with specific arguments for improving the conduct of HCI. This paper provides a means for understanding and articulating the limits of HCI technologies, an important but heretofore under-explored contribution to the field.

Within the last decade, blogs have become an important element of popular culture, mass media, and the daily lives of countless Internet users. Despite the medium's interactive nature, most research on blogs focuses on either the blog itself or the blogger, rarely if at all focusing on the reader's impact. In order to gain a better understanding of the social practice of blogging, we must take into account the role, contributions, and significance of the reader. This paper presents the findings of a qualitative study of blog readers, including common blog reading practices, some of the dimensions along which reading practices vary, relationships between identity presentation and perception, the interpretation of temporality, and the ways in which readers feel that they are a part of the blogs they read. It also describes similarities to, and discrepancies with, previous work, and suggests a number of directions and implications for future work on blogging.

Researchers in information science and related areas have developed various methods for analyzing textual data, such as survey responses. This article describes the application of analysis methods from two distinct fields, one method from interpretive social science and one method from statistical machine learning, to the same survey data. The results show that the two analyses produce some similar and some complementary insights about the phenomenon of interest, in this case, nonuse of social media. We compare both the processes of conducting these analyses and the results they produce to derive insights about each method's unique advantages and drawbacks, as well as the broader roles that these methods play in the respective fields where they are often used. These insights allow us to make more informed decisions about the tradeoffs in choosing different methods for analyzing textual data. Furthermore, this comparison suggests ways that such methods might be combined in novel and compelling ways.

The subconscious influence of framing on perceptions of political issues is well-document in political science and communication research. A related line of work suggests that drawing attention to framing may help reduce such framing effects by enabling frame reflection, critical examination of the framing underlying an issue. However, definite guidance on how to identify framing does not exist. This paper presents a technique for identifying frame-invoking language. The paper first describes a human subjects pilot study that explores how individuals identify framing and informs the design of our technique. The paper then describes our data collection and annotation approach. Results show that the best performing classifiers achieve performance comparable to that of human annotators, and they indicate which aspects of language most pertain to framing. Both technical and theoretical implications are discussed.

Despite the abundance of research on social networking sites, relatively little research has studied those who choose not to use such sites. This paper presents results from a questionnaire of over 400 Internet users, focusing specifically on Facebook and those users who have left the service. Results show the lack of a clear, binary distinction between use and non-use, that various practices enable diverse ways and degrees of engagement with and disengagement from Facebook. Furthermore, qualitative analysis reveals numerous complex and interrelated motivations and justifications, both for leaving and for maintaining some type of connection. These motivations include: privacy, data misuse, productivity, banality, addiction, and external pressures. These results not only contribute to our understanding of online sociality by examining this under-explored area, but they also build on previous work to help advance how we conceptually account for the sociological processes of non-use.