Acta Informatica Pragensia - Forthcoming articles

Fairness-Aware Multimodal Machine Learning for Retail Stock Prediction from Sentiment and Market Data

Sanjay Rastogi, Kamal Upreti, Uma Shankar, Pravin Ramdas Kshirsagar, Tan Kuan Tak, Rituraj Jain, Ganesh Veluswwamy Radhakrishnan

Acta Informatica Pragensia X:X | DOI: 10.18267/j.aip.299165  

Background: The introduction of retail investors to AI-powered trading platforms and especially on emerging markets, has resulted in a new set of risks linked to algorithmic bias and financial forecasting fairness. Social media sentiment and structured data multimodal strategies have demonstrated a potential, but frequently do not have ethical considerations.Objective: This work proposes a multimodal model predictive control (MPC) framework grounded in fairness-based forecasting of next-day returns on stock in stock market settings, particularly ethical behaviour and transparency of the model on retail markets.Methods: We combine BERT-based sentiment...

SKR1: Benchmark for Testing Knowledge About Slovak Realia for Large Language Models

Marek Dobeš

Acta Informatica Pragensia X:X | DOI: 10.18267/j.aip.300170  

Background: To objectively evaluate the capabilities of large language models (LLMs), we need to develop tools that enable such assessment. While numerous benchmarks exist, the vast majority are in English and focus on general knowledge, often overlooking the cultural and factual specifics of smaller countries.Objective: Currently, there is no benchmark that tests LLMs΄ knowledge of Slovak realia. At the same time, LLM performance in this domain remains inadequate. To objectively measure and compare these capabilities, our goal is to develop and validate a specialized benchmark for assessing LLMs΄ knowledge of Slovak cultural and factual...

Artificial Intelligence Applications in Consumer Behaviour Analysis: A Systematic Review, Mapping Trends and Challenges

Adrián No-Pérez, Sandra Castro-González

Acta Informatica Pragensia X:X | DOI: 10.18267/j.aip.30144  

Background: The vast amounts of data generated by consumers require new forms of processing, in which artificial intelligence stands out for its ability to analyse them more quickly and deeply. However, although there is abundant literature on artificial intelligence (AI) and consumption, most of it focuses on its impact on consumer behaviour rather than its usefulness in enhancing understanding.Objective: The aim of this study is to conduct a thorough review of the existing literature on the use of AI to understand consumer behaviour.Methods: This study uses the PRISMA protocol for the selection of the studies. Then, it combines bibliometric methods...

Exploring Design Principles for SME Complementor-Suitable Digital Platforms

Lukas Rudolf Germut Fitz, Jochen Scheeg

Acta Informatica Pragensia X:X | DOI: 10.18267/j.aip.307124  

Background: Some of the world’s most valuable platform businesses rely on products and services provided by small and medium-sized enterprises (SMEs). Though, the modern digital platform economy is increasingly shaped by uncertainties and power asymmetries benefitting dominant platform owners and threatening smaller players participating as complementors in those ecosystems. Negative consequences include lock-in effects and platform dependency, exploitative participation terms and eroded entrepreneurial autonomy on the SMEs’ side, which altogether harm the digital platforms’ long-term viability, too. Addressing these issues, this...