Correlation of variations in geocosmic processes and thinking parameters

Earlier we discovered gender-specific multiyear variations in functional brain asymmetry (FBA) indices, synergistic with variations in geocosmic processes [Volchek, 2013]. FBA serves as a foundation for different types of learning, perception and processing of information. In its turn, type of learning dominating in society manifests itself in social processes, cultural events and working styles of inventors and artists. The purpose of this work was to study thinking and musical creativity indices in relation to geocosmic processes. With Torrance method, we collected data about logical, intuitive and combined thinking styles in over 3400 citizens of St. Petersburg, Russia, born in 1930–1991. Gender-specific daily, seasonal and multiyear variations in thinking indices were revealed at p≤0.001. Content analysis of 3352 Soviet songs and romances composed in 1935–1982 showed evolution of musical thinking.Of special interest is the data on multiyear variations in thinking indices in relation to geocosmic conditions. Significant and reliable variations in thinking types were discovered. For instance, the highest scores for logical thinking type (114.2) were found in men born in 1956, while the lowest scores (82.6) were found in men born in 1959, p≤0.001. According to the results of correlation analysis for the periods of 1940–1991 and 1946–1991, there are correlations between variations in thinking types and geocosmic indices. The most influential factors are Earth’s rotation rate ERR and interplanetary magnetic field IMF. With these indices rising in year of birth and preceding year, scores for left-brain logical thinking type increase, p≤0.001.Conclusion: geocosmic processes influence coordination and activation of human brain hemispheres, as well as leading thinking type in society and evolution of music. Such phenomena can be reflected in social processes up to emerge of periods of so-called Thaw or Cold war

Creating poetry in time perspective

The author discusses the results of a study of multiyear variations in the occurrence of letters in 12,925 pieces of poetry composed by 317 Russian poets in 1796–2012 in correlation with geocosmic weather and of seasonal variations in the occurrence of letters in 2,551 poems by 132 male poets and 30 female poets. The conclusion is that there are multiyear and seasonal fluctuations of the occurrence of letters, which, for virtually all 33 letters, are synergetic with variations in the main indices of geocosmic weather. Temperature, Earth’s rotation rate, precipitation and solar activity indices appear to be the most influential ones, with 23, 17, 17 and 11 correlations, respectively, at p≤0.05–0.001. Seasonal variations in parameters of poetry created by men and by women are significantly different, which reflects gender differences in natural adjustment

Functional brain asymmetry and the proper name

There are several published works on the influence of long-term weak acoustic stimuli onto living organisms and their development. In this context, functional brain asymmetry (FBA) parameters were studied in correlation with the proper name. A. R. Luria sensorimotor tests (the dominant thumb when “locking” hands, the dominant eye, the dominant hand when crossing hands (the Napoleon’s pose), the dominant palm when applauding, the dominant ear) were used. With the data collected, we calculated relative difference in the numbers of the “right” and “left” in the group of certain name bearers for each test, %: thumb – (R-L)t, eye – (R-L)e, hand – (R-L)h, palm – (R-L)p, ear – (R-L)e, total for all tests – Σ(R-L), %. 1,136 men and 2,140 women born in 1920–1991 were examined. With the Fisher’s criterion, significant differences were detected in the bearers of various names, p≤0.05÷0.001, as well as the differences by 1–2 FBA parameters in the namesake persons belonging to different generations (born in 1971–1991 – “young” and born in 1920–1970 – “old”), p≤0.05÷0.001. The conclusion was that among the known functions of the proper name there is also an adaptive function

Adaptive changes in speech perception

The influence of individual characteristics on speech perception was studied in relation to weather conditions. Parameters of emotional and color images for 12 masculine names and 6 vowel sounds were used for experimental models. In the period of 1 February – 7 June 2013, 20 women and 6 men, all residents of St.Petersburg, were filling in a special form, estimating the offered parameters of the emotional image by a 5-score scale and registering their color associations. The data collected during 23 days of the experiment were matched with the indices of local and cosmic weather and compared with individual characteristics: gender, the diurnal chronotype by A.A. Putilov («skylark», «dove», «owl»). Mathematical processing included t-criterion, the Fisher criterion and correlation analysis.Significant and valid adaptive changes in the parameters of images of sounds and names were detected in relation to the part of day, season and weather conditions (p≤0.05÷0.001). Characteristics of the pronunciation of a certain vowel or a name influenced their perception under different environmental conditions. There were significant differences in the studied parameters of speech perception between men and women, which correspond to the higher sensitivity of male organisms to environmental conditions, and between people with different diurnal chronotypes (p≤0,05÷0,001)

Appropriate sounds and words in the light of ecological psychology

Based on the latest evidence of the meaning of individual sounds, we studied multiyear indices of letter-sounds frequency in poetic texts, %, in relation with natural environment conditions of the year they were composed. We analyzed lyrics of 2,300 songs and 1,600 poems written in 1935–1985 and in 1955–2014 respectively. In both cases reliable changes in the variations of each sound frequency were detected by Fisher’s criterion at p≤0.001. Correlation analysis of yearly average speech indexes and geocosmic weather parameters revealed multiple correlations at p≤0.05÷0.001. Apparently, natural environment conditions have an impact on speech and musical sounds production through influencing the psychophysiological state. Consequently, unconscious unity with natural environment helps to find right sounds and right words. The similar process, probably, takes place in the practice of the best traditional healers and psychotherapists

Environmental surrounding and perception of speech

A longitudinal experiment with 26 respondents was conducted to study emotional and color images of 12 men names and 6 vowels. The collected data was studied in association with environmental conditions: the time of the day, local and space weather indices. Most of the studied indices showed significant and valid changes related to the time of the day at p≤0.05÷0.001. Multiple correlations were revealed for the studied indices and environmental parameters at p≤0.05÷0.001

Too authentic to try? The analysis of tourist experiences with authentic food images

Objectives The demand for authentic travel experiences has been stably growing. At the same time, multiple studies highlight the gap between "real" and "staged" authenticity. Tourist product design needs to meet tourists' expectations towards authentic cultural experiences to ensure further engagement. Contemporary technologies provide new opportunities to analyse tourist experiences. This study aims to explore the tourist experience created by authentic food images and identify the factors determining their intention to try this food with the help of combined data from traditional self-report method and sensor-based neurophysiological response data.   Methodology This study builds on the consumer behaviour theory, which states that customers' cognitive and emotional reactions to stimuli influence their behavioural intentions. Guided by this assumption, this study compares the differences in tourists' cognitive and emotional feedback on authentic food between the groups with and without the intention to try this food.   The study was designed as a controlled experiment with 22 participants exposed to 5 cases of authentic food considered exotic to their culinary traditions. The sample with a single cultural background was used to have a homogeneous group. The study recorded neurophysiological response data that indicates visual attention (eye tracking), depth of emotions (electrodermal activity) and range of emotions (facial expression analysis). Then, self-reported perceptions of the experience and intentions to try the food were collected. The data analysis procedures included a quantitative comparison of the attention and emotional reactions between the groups with and without the intention to try this food. Then, the insights were triangulated with the explanatory self-reported data and recorded heat maps.   Main results and contributions The findings indicate that authentic food triggers a range of emotions. However, statistically significant differences were identified only for two components of experiences. Thus, the group with no intention to try the food exhibited a higher rate of disgust with the food details (e.g. heads and teeth of the cooked creatures), while the group with the intention to try demonstrated a stronger interest (number of fixations) to them.   As a theoretical contribution, the study provides a holistic picture of tourists' experiences with food that is authentic for some countries while exotic for them. It further generates explanatory insights into tourist experiences with authentic food with a view to their intention to try this food, thereby contributing to the research on authentic cultural experience.   The findings of this study also offer a practical contribution to destination management organisations and tourism providers in developing tourism experiences centred around traditional local cuisine. Importantly, understanding the determinants of tourists' behavioural intentions, in combination with automated tourist experience analysis, opens the floor for real-time design and delivery of personalised experiences. Therefore, the study provides a forward-looking recommendation for improving tourist business competitiveness.   Research limitations The key limitation of the study is a single context of German tourists. While it allowed the analysis of experience within a homogeneous group, thereby ensuring the data validity, the study's results cannot be generalised to other cultural contexts. More extensive research is required to get a more holistic understanding of the effect of tourists' emotional and cognitive reactions on their behavioural intentions.   Conclusions The study uses a combination of traditional and innovative data collection methods to provide new insights into tourists' emotional and cognitive reactions to authentic food images. The comparison of these reactions revealed that the emotion of disgust and the cognitive interest in the food images are the key differentiating factors that share the tourists' intention to try the food. Understanding the relationships between tourist experiences with food images, together with the automation of data collection and analysis, opens the floor for designing real-time personalised experiences

Generative AI as Sentiment Analysis Tool in Hospitality

Objectives | Customer reviews on social media and dedicated websites are an essential source of information for hospitality companies that allows them to learn what customers think about their services and those of their competitors (Olorunsola et al., 2023; Perez-Aranda et al., 2021; Veloso & Gomez-Suarez, 2023). By analysing online reviews, hospitality managers can get insights into the opinions of customers and what they liked or disliked about the services they used. Moreover, online reviews are a helpful source of information about changing trends in customer perceptions and preferences. The evaluation of customer reviews can be implemented manually or with the help of specialised software (Tetzlaff et al., 2019). Sentiment analysis is a process of analysing language to interpret subjective evaluations, emotions and points of view (Taboada, 2016). Humans associate their opinions and emotions with specific linguistic structures in daily life. Sentiment analysis, therefore, addresses three tasks, including establishing whether the content represents a fact or a subjective opinion, determining its polarity (i.e. positive vs negative), and analysing the degree of polarity/ intensity of a sentiment (Cambria et al., 2017).   The importance of sentiment analysis for research and practice motivated the proliferation of multiple analytical methods and tools, including the automation of the analysis with AI. The advantage of manual sentiment analysis is its high achievable validity and reliability. However, special linguistic skills, substantial time and cross-validation are required to prevent subjectivity bias (Sotiriadou et al., 2014).   A range of tools that utilise supervised learning are trained for automatic differentiation between negative vs positive vs neutral (if required) emotion. The advantage of supervised learning algorithms is the achievable speed of analysis alongside the relatively high accuracy of the results. The limitation of the machine learning algorithms for sentiment analysis is the dependence of the analysis validity on the context. A new training might be required for a new content source (Taboada, 2016).   Recently, ChatGPT introduced a plugin for sentiment analysis (OpenAI.com, 2023). It uses a class of machine learning, called Natural Language Processing (NLP) that is trained to understand a language autonomously.  Due to its cost, speed and intuitive interface, a range of studies has already applied ChatGPT for sentiment analysis of used-generated content (e.g. Adeshola & Adepoju, 2023). The launch of ChatGPT in November 2022 opened a new opportunity for the analysis of texts that do not require significant digital skills necessary to use effectively and efficiently other software packages for textual analysis. However, its performance in comparison to other methods remains largely underexplored (Fatouros et al., 2023). This ongoing study aims to evaluate GenAI as a tool for sentiment analysis in the context of Tourism & Hospitality. It tests the effectiveness of ChatGPT vs NVivo auto coding vs manual analysis.   Methodology To analyse the effectiveness of GenAI as a tool for a sentiment analysis, the study compares the effectiveness of the sentiment analysis, done by ChatGPT 3.5 vs NVivo 20 vs manual coding.  The entire dataset for analysis consists of the 160 reviews posted at Booking.com to ensure that the sentiment is derived from subjective tourist opinions. First, the codes that characterise hotel service robots, were manually extracted to ensure data validity. The sentiment was analysed to determine the polarity of the sentiments and well as its degree. The manual coding, replicated by two trained researchers, was used as a baseline. NVivo auto coding and a prompt “Run a sentiment analysis for each row of the table. The sentiment would range from "very positive", "moderately positive", "neutral", "moderately negative", to "very negative" .” , for ChatGPT, were used to automate the analysis. The number of errors of automated analysis vs manual coding was then calculated.   Main Results and Contributions The preliminary findings demonstrate that ChatGPT performs better than NVivo auto coding but worth than the manual analysis. In comparison to manual coding, ChatGPT provided identical results in determining the polarity of a sentiment (i.e. negative vs neutral vs positive), while 12% of the codes, generated by NVivo, contained a wrongly identified sentiment. Regarding the degree of polarity (i.e. very negative vs moderately negative), ChatGPT generated a total of 24% of erroneous codes. NVivo-generated results were comparable with 28% of wrongly attributed degree of polarity in comparison to the manual coding.       Limitations | The key limitations of the study are the related to the validity of each method and their comparability.   Thus, the manual sentiment analysis required cross-validation, the supervised learning models do range in terms of their relevance for the context, and GenAI represents a “black box” with the model being unavailable for researchers’ evaluation. Therefore, more studies in various contexts and with the application of different sentiment analysis methods are required prior to claiming GenAI a reliable tool for the analysis.   Conclusions The preliminary findings indicate that ChatGPT 3.5 performs substantially better than NVivo auto coding. However, manual evaluation of the sentiment still provides more valid results. While research automation can substantially decrease the time and efforts of the researchers, a broader scale of research is required to understand how to ensure the validity and reliability of the GenAI tools

Tetrasubstituted copper phthalocyanines : correlation between liquid crystalline properties, films alignment and sensing propertie

Copper phthalocyanines (CuPc) containing alkylthio (-S(CH2)nCH3, n=7 and 15), alkyloxy- (-O(CH2)nCH3, n=7 and 15) and polyoxo (-O(CH2CH2O)3CH3 and -S(CH2CH2O)3CH3) substituents were synthesized and investigated to reveal the effects of substituents type (alkylthio, alkyloxy and polyoxo) and the type of the connecting heteroatom (oxygen or sulphur) on the mesogenic properties, films alignment and sensing behaviour. The liquid crystalline properties of these phthalocyanines were investigated by differential scanning calorimetry, polarizing optical microscopy and X-ray diffraction techniques. The structure and morphology of spun thin films of copper phthalocyanine derivatives were studied by the UV-Vis and Raman spectroscopies as well atomic force microscopy. The sensing properties of CuPc films were studied by the measurement of conductivity change upon interaction with ammonia in the range 10-50 ppm. All investigated films of CuPc derivatives display thermotropic columnar mesomorphism. It was shown that the films with polyoxo- (-O(CH2CH2O)3CH3 and -S(CH2CH2O)3CH3) substituents as well as with alkylthio -S(CH2)nCH3 (n=7) substituents, which are liquid crystalline at room temperature, form ordered films with a random planar alignment of columns. Their films exhibit the better sensor performance with the maximal sensor response for the films of CuPc containing (-S(CH2CH2O)3CH3) substituents