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This paper explores how task characteristics in terms of trigger type and task topic influence individual participation in community-based free/libre open source software (FLOSS) development by considering participation in individual tasks rather than entire projects.

A quantitative study was designed using choose tasks that were carried out via the email discourse on the developers' email fora in five FLOSS projects. Choice process episodes were selected as the unit of analysis and were coded for the task trigger and topic. The impact of these factors on participation (i.e. the numbers of participants and messages) was assessed by regression.

The results reveal differences in participation related to different task triggers and task topics. Further, the results suggest the mediating role of the number of participants in the relationships between task characteristics and the number of messages. The authors also speculate that project type serves as a boundary condition restricting the impacts of task characteristics on the number of participants and propose this relationship for future research.

Empirical support was provided to the important effects of different task characteristics on individual participation behaviors in FLOSS development tasks.

The findings can help FLOSS participants understand participation patterns in different tasks and choose the types of tasks to attend to.

This research explores the impact of task characteristics on participation in FLOSS development at the task level, while prior research on participation in FLOSS development has focused mainly on factors at the individual and/or project levels.

Research on artificial intelligence (AI) and its potential effects on the workplace is increasing. How AI and the futures of work are framed in traditional media has been examined in prior studies, but current research has not gone far enough in examining how AI is framed on social media. This paper aims to fill this gap by examining how people frame the futures of work and intelligent machines when they post on social media.

We investigate public interpretations, assumptions and expectations, referring to framing expressed in social media conversations. We also coded the emotions and attitudes expressed in the text data. A corpus consisting of 998 unique Reddit post titles and their corresponding 16,611 comments was analyzed using computer-aided textual analysis comprising a BERTopic model and two BERT text classification models, one for emotion and the other for sentiment analysis, supported by human judgment.

Different interpretations, assumptions and expectations were found in the conversations. Three subframes were analyzed in detail under the overarching frame of the New World of Work: (1) general impacts of intelligent machines on society, (2) undertaking of tasks (augmentation and substitution) and (3) loss of jobs. The general attitude observed in conversations was slightly positive, and the most common emotion category was curiosity.

Findings from this research can uncover public needs and expectations regarding the future of work with intelligent machines. The findings may also help shape research directions about futures of work. Furthermore, firms, organizations or industries may employ framing methods to analyze customers’ or workers’ responses or even influence the responses. Another contribution of this work is the application of framing theory to interpreting how people conceptualize the future of work with intelligent machines.

To introduce the special issue on “Genres of digital documents.” While there are many definitions of genre, most include consideration of the intended communicative purpose, form and sometimes expected content of a document. Most also include the notion of social acceptance, that a document is of a particular genre to the extent that it is recognized as such within a given discourse community.

The article reviews the notion of document genre and its applicability to studies of digital documents and introduces the four articles in the special issue.

Genre can be studied based on intrinsic genre attributes or on the extrinsic function that genre fulfills in human activities. Studies on intrinsic attributes include classifications of genres as clusters of attributes, though these classifications can be problematic because documents can be used in flexible ways. Also, new information technologies have enabled the appearance of novel genres. Studies on extrinsic function include ways to use genre for education or information accesses, as well as the use of genre as a lens for understanding communications in organizations. The four articles in the special issue illustrate these approaches.

The paper provides a framework that organizes the range of research about genres of digital documents that should be helpful to those reading this research or planning their own studies.