Summary statistics of statistical inferences with word tuples.

Summary statistics of statistical inferences with word tuples.</p

Empirical results of top 15 opinionated terms in movie reviews.

Empirical results of top 15 opinionated terms in movie reviews.</p

Summary statistics for hypothesis testing with movie reviews.

Summary statistics for hypothesis testing with movie reviews.</p

Comparison of human classifications to statistical inferences.

Comparison of human classifications to statistical inferences.</p

Empirical results of top 15 polarity expressions in financial filings.

Empirical results of top 15 polarity expressions in financial filings.</p

Additional file 1 of Emotions in online rumor diffusion

S1—Background Literature (PDF 90 kB

Common dictionaries in behavioral research.

Common dictionaries in behavioral research.</p

Additional file 1 of Russian propaganda on social media during the 2022 invasion of Ukraine

(PDF 1.1 MB

Selecting advanced analytics in manufacturing: a decision support model

Advanced analytics offers new means by which to increase efficiency. However, real-world applications of advanced analytics in manufacturing are scarce. One reason is that the management task of selecting advanced analytics technologies (AATs) for application areas in manufacturing is not well understood. In practice, choosing AATs is difficult because a myriad of potential techniques (e.g. diagnostic, predictive, and prescriptive) are suitable for different areas in the value chain (e.g. planning, scheduling, or quality assurance). It is thus challenging for managers to identify AATs that yield economic benefit. We propose a multi-criteria decision model that managers can use to select efficient AATs tailored to company-specific needs. Based on a data envelopment analysis, our model evaluates the efficiency of each AAT with respect to cost drivers and performance across common application areas in manufacturing. The effectiveness of our decision model is demonstrated by applying it to two manufacturing companies. For each company, a customized portfolio of efficient AATs is derived for a sample of use cases. Thereby, we aid management decision-making concerning the efficient allocation of corporate resources. Our decision model not only facilitates optimal financial allocation for operations in the short-term but also guides long-term strategic investments in AATs.</p

Affective Information Processing of Fake News: Evidence from NeuroIS

Fake news undermines individuals’ ability to make informed decisions. However, the theoretical understanding of how users assess online news as real or fake has thus far remained incomplete. In particular, previous research cannot explain why users fall for fake news inadvertently and despite careful thinking. In this work, we study the role of affect when users assess online news as real or fake. We employ NeuroIS measurements as a complementary approach beyond self-reports, which allows us to capture affective responses in situ, i.e., directly in the moment they occur. We draw upon cognitive dissonance theory, which suggests that users experiencing affective responses avoid unpleasant information to reduce psychological discomfort. In our NeuroIS experiment, we measured affective responses based on electrocardiography and eye tracking. We find that lower heart rate variability and shorter mean fixation duration are associated with greater perceived fakeness and a higher probability of incorrect assessments, thus providing evidence of affective information processing. These findings imply that users may fall for fake news automatically and without even noticing. This has direct implications for information systems (IS) research and practice as effective countermeasures against fake news must account for affective information processing.</p