Double the fun - that's why we have the second #Hawaii Paper Alert! ๐จโ๐ฌ๐ด ๐
In "๐ฆ๐ต๐ฎ๐ฟ๐ถ๐ป๐ด ๐๐ถ๐ฒ๐: ๐ ๐ฆ๐ผ๐ฐ๐ถ๐ผ-๐ง๐ฒ๐ฐ๐ต๐ป๐ถ๐ฐ๐ฎ๐น ๐ฅ๐ฒ๐๐ถ๐ฒ๐ ๐ผ๐ป ๐๐ฎ๐น๐๐ฒ ๐๐ป๐ณ๐ผ๐ฟ๐บ๐ฎ๐๐ถ๐ผ๐ป ๐๐ถ๐๐๐ฒ๐บ๐ถ๐ป๐ฎ๐๐ถ๐ผ๐ป," we explored the complexity behind the spread of false information, particularly in the context of social media and information systems.
You can find the full paper here:
https://hdl.handle.net/10125/109630
#fakenews #falseinformation #misinformation #disinformation #propaganda #informationsystems #socialmedia #wirtschaftsinformatik #hicss #hicss2025
This paper provides a comprehensive review of false information dissemination, focusing on factors influencing its spread in the context of social media and information systems. The study synthesizes recent literature to identify and categorize 30 influence factors into eight main categories: demographic, personality-related, psychological, policy- and values-based, informational, media consumption-related, motivational, and preventive factors. Key findings indicate that low education, high extraversion, and conservative values significantly increase false information dissemination. Additionally, social media usage, emotional responses, and information overload play critical roles in promoting its dissemination. Preventive strategies, such as labeling content and training in false information recognition, are also examined. This review aims to improve understanding of the dynamics of false information dissemination and proposes strategies to mitigate its impact.
#Hawaii Paper Alert ! ๐จโ๐ฌ๐ด ๐
Three years in a row at #HICSS, and this year I presented the paper titled 'Leveraging Generative AI and #ChatGPT in SMEs: A Grounded Model' at Waikoloa Village, Hawaii, USA.
The results of this study indicate a productivity increase in multiple #enterprise departments by using #GenerativeAI, especially in #marketing. Improvements in learning processes were noted in #software #development, while #management saw shorter communication pathways.
ChatGPT and other generative artificial intelligence have garnered substantial media attention for their ability to generate text and code, presenting great potential for both personal and professional use. Less research has been conducted in the field of generative AI usage in small and medium enterprises, especially across different enterprise departments. This study examines with a grounded theory approach the characteristics of generative AI usage within management, marketing, and development departments of a small and medium enterprise. Ten employees from this enterprise were interviewed. Three causal and intervening conditions, as well as strategies were identified, to leverage the use of generative AI. The results indicate a productivity increase in all departments, especially in marketing. Improvements in learning processes were noted in development, while management saw shorter communication pathways. Across all departments, significant cost and time savings were observed, along with risks, limitations, and future potential.
Fabian Walke and Thaddรคa Nรผrnberger are "Sharing Lies" ๐ฒ No, this isn't clickbaitโit's the title of our latest research paper, which we'll be presenting at the #HICSS2025 conference ๐จโ๐ซ.
In "๐ฆ๐ต๐ฎ๐ฟ๐ถ๐ป๐ด ๐๐ถ๐ฒ๐: ๐ ๐ฆ๐ผ๐ฐ๐ถ๐ผ-๐ง๐ฒ๐ฐ๐ต๐ป๐ถ๐ฐ๐ฎ๐น ๐ฅ๐ฒ๐๐ถ๐ฒ๐ ๐ผ๐ป ๐๐ฎ๐น๐๐ฒ ๐๐ป๐ณ๐ผ๐ฟ๐บ๐ฎ๐๐ถ๐ผ๐ป ๐๐ถ๐๐๐ฒ๐บ๐ถ๐ป๐ฎ๐๐ถ๐ผ๐ป," we explored the complexity behind the spread of false information, particularly in the context of social media and information systems.
Open data sounds great, but often requires extensive processing. Collaborative data engineering could lower individual participants' effort while increasing data quality, but how are open data users collaborating right now? What challenges do they face?
In a recent paper at #HICSS, we searched articles describing workflows, processes, practices, and participants during data engineering by open data users to find out. You can the whole paper here: https://www.heltweg.org/posts/challenges-to-open-collaborative-data-engineering/.
Our paper โChallenges to Open Collaborative Data Engineeringโ got accepted to the Hawaii International Conference on System Sciences 2023 (HICSS 56). Sadly, we could not present in person due to a flight cancellation but we provided a short video presentation. Abstract Open data is data that can be used, modified, and passed on, for free, similar to open-source software. Unlike open-source, however, there is little collaboration in open data engineering. We perform a systematic literature review of collaboration systems in open data, specifically for data engineering by users, taking place after data has been made available as open data.
David Ing
Dr. rer. pol. Fabian Walke
Jessa Lingel
philip