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This study investigates the relationship between the linguistic and sentimental characteristics of TikTok hooks, which are defined as the brief opening seconds of short-form video content, and subsequent digital engagement levels. The research aims to determine whether the frequency and contextual use of specific lexical features, as well as the emotional tone present in hooks, are associated with key interaction metrics on TikTok, such as views, likes, and comments. To achieve this objective, a dataset of 4983 hooks was compiled by scraping publicly available TikTok content published between January 2020 and December 2022. Audio-to-text transcription facilitated the extraction of linguistic information, which was subsequently analysed via three sentiment analysis methods: Sentimentr, AFINN, and Syuzhet. These methods were employed to capture contextual polarity, affective intensity, and emotional variation. Statistical analyses included Spearman’s correlation tests to assess the relationship between lexical frequencies and engagement metrics, as well as Wilcoxon’s nonparametric tests to compare sentiment profiles between hooks with above- and below-median engagement levels. The findings indicate no statistically significant correlation between the selected lexical features and any of the interaction metrics, suggesting that simple word frequency is not a reliable predictor of user engagement. However, significant differences were observed in sentiment profiles, particularly for the number of views, implying that emotionally charged hooks may be more effective at capturing initial audience attention and may benefit from early algorithmic amplification. These results are consistent with theoretical perspectives from the attention economy, which emphasize the role of emotional salience in shaping user behaviour during the initial moments of content exposure. Several methodological limitations are acknowledged, including potential inaccuracies in audio-to-text transcription, the exclusion of multimodal features such as visual and audio cues, and reliance on lexicon-based sentiment tools that may not fully capture nuanced emotional expression. Future research should incorporate multimodal analysis, semantic modelling, and experimental designs to more comprehensively examine how linguistic, visual, auditory, and algorithmic factors collectively influence engagement patterns on short-form video platforms.

Delving into the intricate world of social media engagement, this comprehensive study analyses the dynamics of user interaction with posts from 5-star hotels on Facebook across the Visegrad Group countries. It meticulously aims to shed light on the variances among engagement metrics—shares, comments, and reactions—across different types of posted content. Furthermore, it explores the complex interrelations among these metrics to provide a holistic understanding of user engagement patterns. In pursuit of this goal, we scrutinized an extensive dataset comprising 10,820 Facebook posts shared by selected 5-star hotels throughout 2019. The data were meticulously collected from the social network utilizing the accessible API, ensuring a robust and reliable foundation for analysis. The investigation employed advanced statistical tools, namely the Kruskal‒Wallis test and Spearman’s rho test, to thoroughly examine and interpret the complex data. The insights gleaned from this research are invaluable, painting a detailed picture of brand management strategies on social platforms. A significant finding of this study is the variation in user engagement levels in relation to the type of content disseminated. It highlights that visual content—specifically videos and photos—tends to dominate in terms of eliciting user responses, as compared to text statuses and links. This underlines the importance of leveraging visual media to captivate and engage the audience effectively. The study also reveals that engagement metrics are intricately linked, suggesting a synergistic effect rather than isolated impacts. This indicates that an integrated approach, considering these metrics as a cohesive unit, could be more beneficial in strategizing content for social media. Understanding these relationships and the dominant role of visual content can greatly inform and transform the way brands, especially in the hospitality industry, navigate their presence on social networks. These findings serve as a guiding framework for optimizing social media content strategies, aiming to maximize engagement and enhance the effectiveness of online brand management.

A comprehensive examination of COBRAs concerning word-of-mouth marketing has yet to be fully conducted. A brand needs to know whether such activities can also entail offline consequences for the brand, i.e. in the form of word of mouth. The distinction between relevant and irrelevant activities is important from the brand’s managerial point of view for cost-effective management and the pursuit of its stated goals. The paper intends to examine the consequences of consumers’ online brand-related activities, along with word-of-mouth marketing, in the setting of the Instagram social network. Instagram is currently a highly effective medium for fostering brand growth in the digital sphere. The dataset comprises 335 standardised questionnaires amassed in the first half of 2021. Based on the current state of the literature and research, together with the research question, one statistical hypothesis was formulated for analysis. The study focused on determining whether certain consumers’ online brand-related activities had a statistically significant effect on word-of-mouth about the brand. The statistical examination of the presented issue made use of Confirmatory Factor Analysis (CFA) employing Maximum Likelihood Estimation (ML) as well as Partial Least Square – Path Modeling (PLS PM). This method was selected based on the fact that the items do not interfere with the internal structure of factors in the instrument, which captures specific aspects of attitudes and perceptions regarding brand-related activities on social networks. The findings revealed that consumers’ online brand-related activities exert two statistically significant effects on brand word-of-mouth, specifically concerning content consumption and content creation, at a 0.05 significance level. The context and potential consequences of this discovery are examined in the concluding discussion section, with reference to existing literature and ongoing research.

Tourism is one of those segments where the effect of implemented innovations tends to show relatively quickly. The presented study aims to assess the links between knowledge and technological innovation and tourists' spending in a sample of developed countries. To this end, the research relied on annual data (2010-2019) from selected OECD countries (n = 36). Data presenting the innovation potential (Knowledge & technology Global Innovation Index) of selected countries (knowledge creation, impact of knowledge, and knowledge diffusion) was included in the analyzes. Four indicators represented tourism: Business Tourism Spending, Leisure Tourism Spending, Domestic Tourism Spending, Visitor Exports - Foreign spending. The panel regression analysis showed that demonstrable links were proved only for some assumptions, while the identified effects acquired negative trajectories, i.e., in countries where higher tourist spending was identified, lower outputs of innovation activities in the examined areas can be expected. In addition, significant negative links were discovered between the indicators of the creation of knowledge and visitor exports, as well as the dissemination of knowledge and domestic tourism spending. For more accurate results, further analyzes and examinations of interconnections in a different country structure are needed.

The main goal of the paper is to assess the statistical significance of the differences in the motives and activities of COBRAs in the context of the frequency of use of these platforms and also the driving forces and motivations behind the brand-related activities. The importance of consumers’ online brand-related activities (COBRAs) as relevant factors in managerial and marketing practice is undeniable. In addition, this area is only at the beginning of research coverage, and thus defines a research gap for us. The dataset used hereunder is based on data acquired from a standardized questionnaire discussing the above-mentioned activities and motives. In total, the questionnaire was filled in by 401 respondents. The analysis made use of the Kruskal–Wallis H test to detect differences and the Spearman’s rho coefficient to detect relationships. Based on this, several statistically significant differences and relationships were identified in all cases. The most important implications drawn pertain to differences in the social-interaction motives on all platforms studied, the highest rate of concurrence, at the level of 3–4 h, spent on these platforms, as well as relationships with a strong correlation coefficient in content-creation activities and content-contribution activities on all social media platforms. Even though these findings require further analysis, they prove a valuable insight into the topic.

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The method of categorizing consumers’ online brand-related activities (COBRA) is a relatively recent finding in marketing research. Based on this, there is a need for further exploration of a related issue. One of these is the relational link between COBRAs and consumer motivations for these activities. With this research, this study aims to assess the statistical significance of such trajectories of relationships of the motivations on consumers’ online brand-related activities related to all three levels of brand-related content activities in terms of the social network platform Instagram. These motivations have origins in the uses and gratification theory. Three levels of analyzed activities are the most recent comprehensive classification. The research database was made up of responses from 335 online questionnaires. The collection of data was carried out in the 1st half of 2021. Primary data were analyzed using confirmatory factor analysis and PLS PM (Partial least squares path modelling) equations, while average variance extracted metric and composite reliability were used to describe the suitability of the latent variables that entered the analysis. For the analysis, four research hypotheses were formulated dealing with 12 partial trajectories of relationships, of which only three trajectories were not statistically significant. However, at least one significant trajectory was identified for each motivation, allowing us to confirm all formulated hypotheses. The findings of the analysis supported the claims of the existence of statistically significant effects for all the motivations investigated against consumers’ online brand-related activities. The obtained results also identified social interaction as the strongest motivator. The authors discussed the potential drivers and implications for theory and practice in a separate section, comparing with existing related research. The most significant contribution of this research is considered to be the confirmation of the exploratory findings that link COBRA activities and motivations on a scale that has not yet been analyzed (by this we mean 3 levels of activity and 4 categories of motivation). This formed the basis for this investigation, and the results obtained are in agreement.