Neuromarketing applied to communication as neurocommunication in WOS: bibliometric reviews and a guide to the first twenty years of the 21st century, from 2001 to 2020

doi:10.21203/rs.3.rs-3242390/v1

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Neuromarketing applied to communication as neurocommunication in WOS: bibliometric reviews and a guide to the first twenty years of the 21st century, from 2001 to 2020

https://doi.org/10.21203/rs.3.rs-3242390/v1

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The objective of this article is to carry out a bibliometric study on the scientific publications on neuromarketing applied to communication as neurocommunication that have been indexed in the WOS database, from the year 2001 to the year 2020 (inclusive). Initially, a search was carried out in said database with the terms neurocommunication, neuromarketing and consumer neuroscience, filtering the last two terms with the word neurocommunication, to later carry out a basic bibliometric study. Subsequently, the articles that effectively dealt with neuroscience applied to the evaluation of business communication, whether external or internal, were selected and a brief description of them was made. It is hoped that it will be a document that serves as a practical guide for readers who wish to get a global idea of the existing knowledge in WOS about this new neurodiscipline and that will help them select the papers that may interest them if they so wish to get started in this area of knowledge or if you are looking for the procedure to perform a particular type of experiment with any neurocomunication techniques.

Marketing

Cognitive Neuroscience

neuromarketing

consumer neuroscience

neurocommunication

marketing

comunicación

Communication understood as a superior cognitive process of the human being has been widely studied and defined from different perspectives and theories, from philosophy to neurology, from its basic components, its organic structures, its modalities and its uses, to its applications.

In recent years, technology has evolved in such a way that it has been possible to study brain activity associated with communication and other daily activities related to companies and organizations. One of the fields in which the advances made by neuroscience have been most studied and applied has been marketing.

Initially, the current study began to be carried out on the articles that were indexed in the Web of Science (WOS) under the keyword neurocommunication, but almost all the works indexed under this keyword referred to questions about communication between neurons and other biological and physiological issues, with very few results related to the object of study of this article: discipline of business communication and/or marketing. But given that communication is one of the four variables of operational marketing, the search was complemented with the term neuromarketing and later the studies that dealt with some of the components of communication were filtered, mainly because most of the articles have been published under the keywords neuromarketing and consumer neuroscience. Therefore, the bibliographic search was carried out with the terms "consumer neuroscience", "neuromarketing" and "neurocommunication".

Consumer neuroscience "is an emerging interdisciplinary field that combines psychology, neuroscience, and economics to study how advertising and marketing strategies physiologically affect the brain" (Lee, Broderick, & Chamberlain, 2007; Madan, 2010). “It links consumer choices and decision-making with market research, the study of the neural conditions and processes underlying consumption” (Camerer, Loewenstein and Prelec, 2004; Pirouz, 2004).

The Spanish Association of Neuromarketing and Neurocommunication (AENENE) defines Neuromarketing as "the application of neuroscience to facilitate and improve the creation, communication and exchange of actions, services and products of value between groups and people who need and want to meet their needs through these exchanges'' (González-Morales, 2020; González-Morales, Mitrovic, & Garcia, 2020).

The definition of “neurocommunication” is difficult to specify and none of the authors consulted offers a specific definition of it. The author considers that it is necessary to define this term according to the function it fulfils in the case that he deals with in this article and leaving aside what can be defined from a medical, biological or neurological point of view. Therefore, it proposes that neurocommunication is the use of neuroscience techniques to evaluate the perception that people have of communicative stimuli or of any part or component thereof, from the point of view of communication attraction and the emotions they generate.

Once these concepts have been defined, a bibliometric study is proposed to shed light on the state of the art of neuromarketing (communication variable) and neurocommunication, since up to now there is no similar article that does this work with the keywords used and also provides a guide with the one that the reader can make a first approach to the published articles without the need to search one by one, which is a great help when starting out in a field of knowledge. For this, the present work is structured as follows: in the following section 2 the materials and methods used for the bibliometric analysis are specified. Then, in the third section the results are specified. In section 4, a discussion of the findings is carried out and the main conclusions are drawn, paying attention to the publications, the journals, the techniques and the authors. A brief guide and description of the application articles is proposed in the next section. Finally, the main limitations and future research lines are presented.

2.1 Material

The review has been carried out on the articles indexed in the Web of Science (WOS).

2.2 Methods

The methodology followed in this review was structured in this way:

Search: The search for articles in the Web of Science (WOS) database was carried out during the months of December 2020 and January 2021 under the three terms mentioned above: neuromarketing, consumer neuroscience, neurocommunication and their combination.

Filtering: A screening of the articles was carried out to avoid duplicities that could err the descriptive data, detect possible errors derived from the information dump, verification of the techniques and equipment used in the experiments and other data of interest that would serve for a selection of the finest articles.

Reading: They were read to know what was studied in each one.

Descriptive statistics: A basic descriptive statistical study was carried out to provide readers with information on the evolution, size and other questions about scientific production in this field of knowledge.

Obtaining conclusions: Analysis and extraction of general and descriptive conclusions of the documents.

Initially, different searches were carried out in the WOS database with the following combinations of words to find all the articles referring to the evaluation of communication through neuroscience:

Neuromarketing > Communication
Consumer Neuroscience > Communication
Neurocommunication

It would have been possible to use other keywords, such as EEG or other keywords referring to techniques used in neuromarketing and neurocommunication, but the results of these searches yielded a large number of results, the vast majority of which were not dedicated to neuromarketing or neurocommunication, so it was decided to focus the search on the keywords used, since the important thing is not the tools themselves, but the use of these tools in neuromarketing and neurocommunication.

A review of the literature has been carried out through a cross-sectional exploratory research with a qualitative approach, through which the scientific contributions are collected under the term “neurocommunication” collected in the different bibliographic sources.

The review has been carried out on the articles indexed in the Web of Science. In our case, the works are considered as "production units" of scientific knowledge (Talukdar and Arihanan, 2011).

The search was carried out for the period of time from the year 2001 to the year 2020. In the referred searches, a total of 167 different articles were analysed.

The information extracted from the articles analysed was, in addition to that necessary for the bibliometric review; the equipment and/or techniques used for the experiments; the type of application; free access; most frequently used equipment in experimental papers; the annual distribution of publications by used technique in experimental papers and a brief description of the insights gained that is detailed in the last section of the article, which could help readers to select the experimental articles of interest to them.

We think this is unusual for this type of article, but sometimes we have thought that if other articles we used in the past had had this, it would have helped us.

An interesting variable was whether neuroscience was applied to the evaluation of communication or marketing (communication variable), since some articles framed in these areas deal with other issues. For this, all the articles have been analysed and under the criteria set out below, a membership table has been made.

Membership / inclusion criteria:

Documents of experiments with the use of equipment used in neuroscience related to marketing, consumption and advertising, which finally yield useful data for research in these fields and their practical application.
Articles that, even though they are not experimental studies, are correlational studies or field studies that have been considered relevant.
Articles that raise necessary debates about the ethics, legal and social implications (ELSI) of the use of the advances derived from the studies in these fields and that it is necessary to take into account to carry out the experiments.

Membership / exclusion criteria:

Documents related to other fields outside the scope of this article.
Documents that were part of specific investigations related to the medical, psychiatric, engineering, statistical, biochemical and other similar fields.
Documents that, even being applied to the areas marked as preferred studies, focus only on technical, statistical, methodological or specific operating issues of the equipment used in neuroscience.

3.1 Global Results

Next, the bibliometric analysis will be carried out on various aspects of the global searches carried out.

Number of documents: 167 different articles were found that are distributed in the three areas, with the temporal distribution according to Table 1 and Fig. 1. Compared to the other fields, neuromarketing shows a more pronounced growth.

Free access: Considering the open access of the articles, they are distributed according to the different areas as detailed in Table 1.

Table 1

Articles that within each area are related to the term neurocommunication, annual distribution and by areas of published works and distribution of free access articles by areas.

Source: Own production.
Year	Number of documents according to research field
Year	Consumer Neuroscience			Neuro- communication			Neuro- marketing		Total/Year
2020	7			2			7		16
2019	7			2			19		28
2018	5			0			14		19
2017	9			2			17		28
2016	1			2			6		9
2015	1			0			10		11
2014	5			1			7		13
2013	2			0			2		4
2012	2			2			4		8
2011	2			1			6		9
2010	2			0			2		4
2009	1			0			2		3
2008	1			0			1		2
2007	1			1			1		3
2006	1			0			0		1
2005	0			1			1		2
2004	1			1			0		2
2003	1			1			0		2
2002	0			2			0		2
2001	0			1			0		1
Subtotal	48		21			98			167
Open Access	Yes	No	Yes		No	Yes		No	Yes	No
	33	15	14		7	61		37	108	59

Authors with the highest number of publications: Fabio Babiloni (Sapienza University of Rome) and Giovanni Vecchiato (Sapienza University of Rome) with 8 documents.

Journals with the highest number of publications: Journal of Advertising Research (11 documents) and Ethics and Neuromarketing: Implications for Market Research and Business Practice (10 documents).

Number of documents that belong (those that really deal with neuroscience applied to the evaluation of communication or marketing): 167 different articles were found, although according to the membership data, there are only 135 that really deal with neuroscience applied to communication or marketing as is understood in this paper (see Table 2).

Table 2

Articles that within each area really belong to neurocommunication, as understood in this article and number of articles that really belong to neurocommunication, as understood in this article and have open access.

Source: Own production.
Research Field	Belonging / No Belonging	Number of documents
Consumer Neuroscience	No	7
Consumer Neuroscience	Yes	41 (12 Open Access)
Neurocommunication	No	14
Neurocommunication	Yes	7 (4 Open Access)
Neuromarketing	No	11
Neuromarketing	Yes	87 (32 Open Access)
Total		167

It is necessary to say that the bibliometric study has been carried out from all different WOS outputs with the search terms indicated above, as this is what the reader will find in WOS. Although it should be known that of these outputs, there are actually some papers that do not deal with neurocommunication, as understood in this article. So this difference is included so that the reader is aware and pays maximum attention. This bibliometric study could have been done only with the papers that the research team considers neurocommunication, but there may be different opinions from other readers and reviewers. In addition, the reader might think that the study is poorly conducted if he/she finds that the number of articles indicated in this research and the number of articles obtained from WOS are different, without having read the article in depth. And it could also be called neurocommunication, but for other branches of knowledge. It should be noted that the proportions of articles not considered as neurocommunication articles in each research field used by the research team are provided, so that the reader can get a real idea of all the bibliometric information.

Of the articles that belong to the concept of neurocommunication as it is understood in the article (belong) have open access (see Table 2).

Mostly used or cited equipment: The most frequently used Neuroscience equipment in any of the fields are EEG (46 articles), Peripheral meters (25 articles), Eye Tracker (19 articles) and fMRI (11 articles). The annual distribution of publications by used or cited technique is described in Fig. 2.

3.2 Search results by research field

- Neuromarketing > Communication

Number of works found: a total of 98 articles have been found, of which 87 have been considered to be about neurocommunication, as understood in this article, therefore 11 documents should not be included. The temporal range of the articles found and included in this area of the study goes from 2009 to 2020; from 2001 to 2008 there is no indexed work.

- Consumer Neuroscience > Communication

Number of papers found: a total of 48 articles have been found, of which 41 have been considered to be about neurocommunication, as understood in this article, therefore 7 documents should not be included. The time range of the articles included in this area of the study extends from 2002 to 2020: in 2001 there is no indexed work.

- Neurocommunication

Number of works found: a total of 21 articles have been found, of which 14 have been considered to be about neurocommunication, as understood in this article, therefore 7 documents should not be included. The time range of the articles included in this area of the study extends from 2007 to 2020, in 2001 there is no indexed work.

Temporal distribution of the works included in neurocommunication as understood in this article by research field can see in Fig. 3.

Neurocommunication can feed, derive or overlap with other neurodisciplines, specifically with neuromarketing and with consumer neuroscience. Proof of the overlapping of knowledge and articles between these disciplines is the duplicity of articles analysed in one or more areas of those reviewed in this article.

The documentary searches carried out through the term neurocommunication or neurocommunication (in Spanish) do not provide any results in the first case and a small number of them in the second, 21 papers. Neuromarketing provides 98 papers and consumer neuroscience 48 papers. Only 7 papers from neurocommunication, 41 papers from consumer neuroscience and 87 papers from neuromarketing are really interesting for communicationprofessionals and researchers .

In the cases of Neuromarketing and Consumer Neuroscience, which are the neurodisciplines that currently contribute the most scientific knowledge, they should be taken into account from other disciplines in which the knowledge created by them can be applied, such as, for example, in education, psychology and other disciplines that could feed on it, in order to improve research efficiency.

4.1 About the publications

It is not until 2002, when the term neurocommunication is applied to neuroscience articles applied to consumer science and the measurement of emotions through neuroscience equipment, being from the last decade when there has been a greater growth in the number of articles published on these matters.

It has been verified that since 2014 the number of publications referring to neuroscience and its applications such as neurocommunication, neuromarketing and consumer neuroscience has increased considerably. Between 2010 and 2014 the publications were 5 per year and in previous years only 2 per year.

There is a greater participation in conferences, more research and more researchers in Neuromarketing than in consumer neuroscience and neurocommunication, in such a way that neuromarketing articles account for more than half of the total articles analysed, 88 of a total of 135 articles on neurocommunication as understood at work and 167 articles found.

4.2 About the journals

Of the articles selected for this review, 64.67% of the articles have open access.

The Journal of Advertising Research is emerging as the one with the highest number of publications in all areas with 11 papers, then Ethics and neuromarketing: implications for market research and business practice with 10 papers and finally Comunicar with 7 papers.

Ethics and Neuromarketing: Implications for Market Research and Business Practice is one of the media that has published the largest number of articles related to these matters in question, demonstrating the great interest and importance of ethics and values in these areas.

4.3 About the techniques

The most widely used technique is electroencephalography. The popularity of the EEG as a study instrument occurs both in its use alone and in combination with other techniques such as the eye tracker and peripheral meters. There are 34 experimental articles in which electroencephalography has been used, 10 in which the eye tracker has been used and two in which the micro-expressions detection software has been used. Of those of peripheral meters, only one has been described, since the rest dealt with a methodology that is named under a commercial brand and has not been taken into account in order to keep the article as neutral as possible in terms of commercial interests. It must be said that in articles classified as EEG or eyes tracker, researchers have in some cases combined these techniques with other techniques.

4.4 About the authors:

The most prolific authors are F. Babiloni (Sapienza University of Rome) has published 8 papers and G. Vecchiato (Sapienza University of Rome) has published 8 papers

The findings of this study considers that knowledge about neurocommunication is very segregated and unconsciously camouflaged in titles that are sometimes difficult to detect, it not being possible to get a clear idea about the knowledge it provides and the work carried out. This makes it difficult for some new researchers in the field and new professionals who want to start training in it, to reach it.

After ruling out studies on brain biochemistry, emotional disorders, disorders, articles on marketing in which neurosciences are not used, those on Inbound Marketing and audience metrics, communication between neurons and some articles that mention neuromarketing without further ado, but they are not really about neuromarketing.

Those experimental works that carry out applications of neuroscience to marketing/communication with different techniques have been selected, eliminating several articles in which predictions of attention and emotion were made through the WWTP, as it is a procedure and technology under a certain commercial brand.

Below is an enumeration and a brief description of the experimental works on neurocommunication applications in any of their conditions with brief reviews of the equipment they use, a brief description and the results obtained ( if these could be generalised), so that they guide the reader. These works are grouped into different sections, according to the main technology-technique used, although on some occasions both are combined (see Table 4).

Table 4

Experimental works that carry out applications of neuroscience to marketing/communication.
EEG
Thammasan, Brouwer, Poel, & van Erp (2020)	It studied EEG synchrony between people using hyperscanning (two EEGs, one placed on each of the participants) to reveal synchronous brain mechanisms of two people perceiving the same auditory stimuli. It shows that there is synchrony in the EEG signals between several people who receive the same stimulus. A high potential to know what happens during purchases is assumed, but this knowledge is still being investigated.
Read (2019)	Using EEG using ERPs evaluated images for a national advertising campaign. Each image featured two women, two men, or a man and a woman in positions of intimacy. Brain event-related potentials (ERPs) associated with attention did not differ by partner composition. However, ERPs associated with working memory and emotion were increased by images with two men. The preference was confirmed in the self-reported attitudes.
Liao, Zhang, & Peng (2019)	Through EEG using ERPs, the positive and negative comments on social networks about products have been studied, proving that exposure to comments moderates the social influence of product approval. Behavioural results indicate that gossip about a close friend or celebrity (relative to a stranger) and positive gossip (versus negative) increase consumer willingness-to-pay after product approval, respectively.
Libert, & Van Hulle (2019)	Using a method to predict from EEG data whether individuals will decide to avoid viewing a trailer. Concluding that EEG can provide indications of viewer interest and skip behaviour.
Golnar-Nik, Farashi, & Safari (2019)	Using EEG and assessing the PSD has studied consumer preferences and the interpretation of changes in consumer decision-making in the purchase when the content of an ad is changed, including background colour and promotions. Using PSD it is possible to predict consumer decision making with relatively high accuracy, distinguishing between "I like" and "I don't like". Adding the background colour to the designed ad had a negative impact on liking a product.
Casson, & Trimble (2018)	It showed that the EEG records movement artefacts. This article proposes a new multimodal detection approach to analyse EEG collected during free movement tasks. Co-registered eye fixation and handheld gyroscope data are used to identify times of interest for analysis and movement times, analysing only time periods in which the eyes fixate on the desired stimuli and there is a pause natural in the movement of the subject.
Casson (2018)	It carried out a study using EEG with movements in a clothing store, obtaining different conclusions.
Ogino & Mitsukura (2018)	The hedonic valence of a single-channel electroencephalography product was evaluated prior to its market launch.
Doborjeh, Doborjeh, & Kasabov (2018)	It modelled and visualised brain activity patterns generated by product features with respect to spatio-temporal relationships between continuous EEG data streams using brain-like neural network models (SNN) to analyse the spatio-temporal brain patterns generated by the attentional bias. Consumers are more likely to be distracted by product features that are related to their subconscious preferences. Consumers pay the most attention to non-target stimuli when presented with attractive features. This study is evidence of the role of attentional bias in human preferences related to worry.
Shen, & Morris (2016)	It proposed a procedure that combines a visual self-report scale with functional magnetic resonance imaging (fMRI) to measure emotional response to television commercials. They demonstrated the importance of the three key dimensions of emotion (attractiveness, engagement, and empowerment) in measuring sentiment about advertising.
Teo, & Chia (2018)	It studied the use of machine learning approaches to detect human emotion through electroencephalography (EEG) while immersed in an immersive virtual reality environment. A roller coaster was used. It deals with the application of learning algorithms for the evaluation of arousal.
Kang, Cho, Park, Jun, & Yoon (2017)	It applied the use of EEG to improve the user experience on display screens.
Yadava (2017)	It proposed a predictive modelling framework to understand consumer choice towards e-commerce products in terms of "likes" and "dislikes" by analysing EEG signals. The choice prediction accuracy was recorded using a user-independent testing approach with the help of the Hidden Markov Model (HMM) classifier. It have found that the prediction results are promising and that they can be used to improve the business model.
Pozharliev (2017)	It offers advertising researchers a series of research programs on the key indicators of advertising effectiveness (attention, emotion, memory and preference) explaining the influence of society on advertising effectiveness and on physiological reactions, which is left out in neuromarketing laboratory studies.
Gupta, Shreyam, Garg, & Sayed (2017)	Preferred soap brand was assessed by EEG using four video advertisements. Subjects prefer a certain brand of soap.
Clerico, Gupta, & Falk (2015)	It proposed that to characterise emotional states with EEG, spectral power, coherence and frontal asymmetry are used, as well as the measure of cross-frequency coupling. The authors propose a new feature set that combines some of these paradigms that outperform conventional experimental results in estimating the affective dimensions of arousal, valence, dominance, and liking when these are merged with the spectral power and asymmetry index features, which suggests the complementarity between the spectral and spectrotemporal features.
Morillo, García, Gonzalez-Abril, & Ramirez (2015)	It has carried out a study to find out how the brain responds, through EEG, during the viewing of advertising short films. By using discrete techniques on EEG frequency bands of a labelled data set, C4.5 and ANN learning methods have been applied to obtain the score assigned to each ad by the user. This technique makes it possible to achieve more than 82% accuracy, with low-cost EEG.
Vecchiato (2014)	It provided a novel method to estimate the level of memorization that occurs in the subjects of television commercials. In particular, the present work introduces the Peak Density Function (PDF) as an electroencephalographic (EEG) temporal variable that correlates with the brain events of memorization of television commercials. The present results show that the increase in PDF is positively correlated, scene by scene, with the subjects' spontaneous recall.
Yılmaz, Korkmaz, Arslan, Güngör, & Asyalı (2014)	It studied the EEG frequencies and channels that could be better indicators of preference when viewing different photographs of shoes in terms of like and dislike, as well as the temporal characteristic of "pleasant" decisions during such mental processes, finding the most discriminating frequency bands and channels.
Murugappan, M., Murugappan, S., & Gerard (2014)	It studied the preferred car brand in Malaysia through EEG signals. Using a feature vector that is further provided to two nonlinear classifiers, namely K-Nearest Neighbor (KNN) and Probabilistic Neural Network (PNN) to classify subject intent in ads. Obtaining that the maximum average classification rate of 96.62% is achieved using the PSD function and the PNN classifier marketing communications.
Wriessnegger, Hackhofer, & Müller-Putz (2015)	They conducted a pilot study with EEG using ERPs to detect like/dislike decisions in stimuli from the automobile sector.
Kaur, Gill, & Singh (2019)	It studied EEG advertising videos using deep learning (DL) and support vector machine (SVM) classifiers. The deep learning network gave more accurate results than the SVM.
Khushaba, Wise, Kodagoda, Louviere, Kahn, & Townsend (2013)	It studied physiological decision processes with EEG and eye tracker while participants performed a cookie decision task. The two main objectives of the research were (1) to observe and evaluate the cortical activity of the different brain regions and the interdependencies between the electroencephalogram (EEG) signals of these regions; and (2) provide a way to quantify the importance of different cookie features that contribute to product design based on mutual information. The analysis indicated that the various cookie flavours and toppings were more important factors influencing the purchase decision than the cookie shapes.
Sands, S. F., & Sands, J. A. (2012)	They have performed an EEG experiment while participants moved freely in a shopping environment while EEG was monitored, developing a technology that allows discrete EEG measurement.
Vecchiato, Kong, Giulio Maglione, & Wei (2012)	It studied the cognitive process before advertisements using electroencephalography (EEG) and intensive signal processing techniques for the evaluation of advertisements, providing information related to memorization and attention.
Vecchiato et al. (2011)	It studied frontal asymmetries by means of the power spectral density (PSD) of the EEG during the observation of commercial videos. In the analysed population, power spectral density (PSD) maps showed an asymmetric increase in theta and alpha activity related to the viewing of pleasant (unpleasant) advertisements in the left (right) hemisphere. A correlation analysis revealed that increased PSD at left frontal sites is negatively correlated with the degree of perceived liking. In contrast, desynchronization of left frontal alpha activity is positively correlated with judgments of high degree of liking.
Gupta, & Falk (2016)	It studied brain signals using EEG in music videos, verifying a complex interaction of information transfer between various brain regions, characterising three emotional classifications: valence, arousal and dominance, as well as subjective classification of "taste". Graph-theoretical features were used to classify emotional states through support vector machine (SVM) and relevance vector machine (RVM) classifiers. Overall, our study shows that EEG graph-theoretic features are more suitable for emotion classification than traditionally used EEG features, such as power spectral features and asymmetry index features.
Vecchiato et al. (2010)	It present some considerations on the use of appropriate statistical techniques in the framework of brain mapping as protection against type I errors. The use of the Bonferroni or Bonferroni Holm adjustments correctly returned the absence of differences between the signals collected from a mannequin A partial sample of the recently published literature in different neuroscience journals suggested that at least 30% of the papers do not use statistical protection for type I errors.
Vecchiato et al. 2011	They made a general description of some articles of interest for market research that use electroencephalogram (EEG) and magnetoencephalogram (MEG) methods. The interest in these methodologies lies in their high temporal resolution as opposed to the investigation of this problem with the functional magnetic resonance imaging (fMRI) methodology. An example of how EEG could be used to analyse cultural differences between making video commercials for carbonated beverages in Western and Eastern countries is also shown.
Baraybar-Fernández (2017)	It studied audiovisual advertising messages that represented the basic emotions: joy, surprise, anger, disgust, fear and sadness, and two rational messages through echocardiography (ECG) and electrodermal activity (EDA) of the subjects, on the one hand; and on the other, she used a conventional research technique through a questionnaire, obtaining different conclusions.
Teo, Chew, Chia, & Mountstephens (2018)	They combined electroencephalography with deep learning to improve the evaluation of emotions in the face of different 3D visual stimuli.
Vecchiato et al. (2014)	They conducted a study of television commercials using electroencephalogram (EEG), galvanic skin response (GSR), and heart rate (HR). He determined different cognitive and emotional indices of individuals.
Eye Tracker
Huang, & Kuo (2020)	They carried out an experiment using eye tracking to study emotions, the priming effect and inertia in buyers' decision making
Liaudanskaitė, Saulytė, Jakutavičius, Vaičiukynaitė, Zailskaitė-Jakštė, & Damaševičius (2018)	It studied eye movements, fixation times, gaze fixation locations, and areas of interest in advertising images with eye tracker, as they are good predictors of customer behaviour. The results are known to show that there are statistically significant differences in how affectively charged images are perceived, but no statistically significant differences between genders have been found when shorter fixations representing unconscious processing of visual information are analysed.
Muñoz-Leiva, Hernández-Méndez, & Gómez-Carmona (2019)	It studied the effectiveness of social media advertising in terms of visual customer attention and self-reported recall on tourism websites using eye trackers and questionnaires. Measures of visual attention based on eye-tracking data differed from measures of self-reported recall. Visual attention to the banner ad was paid at a low level of awareness, which explains why associations with the ad did not trigger later recall.
Cuesta-Cambra, Mañas-Viniegra, Niño-González, & Martínez-Martínez (2019)	It analysed the cognitive processes carried out by university students on advertising in relation to compliance with the self-regulation code. For this, a qualitative and quantitative methodology based on eye-tracking techniques, facial expressions of emotion and discussion groups have been used. The results reveal that the operators of online games are clearly identified, with high public interaction with the welcome bonuses and the display of the supposed skills of the successful player; a trivialization of gambling addiction; a lack of awareness of visual elements; and a sexist treatment of women that attracts public attention.
Clark (2018)	They conducted a study on mobile advertising and mobile user experience using visual fixations, heart rate, electroencephalography, skin conductance, and facial affect. The results showed that there are three practises that lead to a positive user experience with ads: maintaining the user's willingness to interact with ads, limiting the disruptive nature of ads, and encouraging viewing.
Mañas-Viniegra, González-Villa, & Llorente-Barroso (2020)	They carried out a study with eye tracker and galvanic skin response to find out the attention and emotional intensity felt by young Spanish university students when visualising the corporate purpose in front of the corporate visual identity, as well as the image of the President of the main Spanish companies listed on the IBEX 35. The brands with the highest brand value in the Interbrand ranking (2019) are those that receive the highest levels of attention and emotional arousal, and that a well-formulated corporate purpose is not enough to satisfy the public if the company's credibility is low due to prior perceptions of an organisation.
Cuesta-Cambra, Niño-González, & Rodríguez-Terceño (2017)	It studied through Eye Tracking and EEG, the attention and processing of the educational content of an APP, as well as its consequences on learning through them. Recall and liking for stimuli were also analysed. It was found that there is a different pattern of visual activity between men and women that does not affect later recall. Recall is determined by the emotional value of the image and its simplicity: more complex images require more visual fixation time but are remembered less. They confirm the importance of the playful component of memory and low-involvement processing. The behaviour before an educational app is of low involvement as in advertising.
Mañas-Viniegra, García-García, & Martín-Moraleda (2020)	Using eye trackers have compared emotional journalism using drones that allow access to dangerous or difficult places versus traditional journalism. The results suggest that attention was focused on the most spectacular visual elements, although the images shot with a drone received a higher concentration of attention from the subjects.
Añaños-Carrasco (2015)	It studied advertising through eye tracker, which combines conventional advertisements with advertising formats included in the program that do not break its continuity, non-conventional advertising (PA). It was analysed in elderly people and in terms of capturing attention, maps of heat and eye fixations. Content recognition, level of psychological reaction to UA, and channel skipping behaviour were also analysed, concluding that cognitive aging does not affect both the ability to pay attention to integrated content and the ability to process information.
Breninger, & Kaltenbacher (2020)	It studied using eye tracker and galvanic skin response to analyse ethical creativity as a process of intersection with the development of intercultural expertise in leaders of small and medium-sized companies and non-governmental organisations (NGO). The experiment consisted of 40 affective and culturalized visual items. "Ethical creativity" is seen as a dynamic process arising from the joint activation of benevolent moral mindsets. The process of becoming interculturally competent and being able to practice ethical creativity is linked to advertising campaigns. These interactions (of perception with activation of mindsets) have the potential to profoundly shape consumer behaviours and understanding.
Peripheral meters
Monge-Benito, Olabarri-Fernández, Usin-Enales, Etxebarria-Gangoiti, Horna-Prat, & Mínguez (2019)	The study was carried out to explore the effectiveness of audio-visual advertising in the Basque population according to the language used, the minority language (Basque) or the dominant language (Spanish), by means of questionnaires and psychophysiological measures.
Microexpresions detection software
Goyal and Singh (2018)	The study shows how advertising on products is evaluated using a microexpression detection software.
Filipovic, Despotovic-Zrakic, M., Radenkovic, Jovanic, & Živojinovic (2002)	The study proposes that artificial intelligence applied to emotion detection in neuromarketing. This article describes how the detection process works and an evaluation using an experiment. The results show that the user's emotions can be recognized by the developed system with a satisfactory level of precision. The advertising content has previously entered parameters, which represent the desired results. Comparing these parameters and the results obtained, the marketer can decide whether to use the ad.
KM, Rajendran, Wan, Panetta, & Agaian (2019)	The study proposes that facial emotion recognition technology focuses mainly on visible spectrum information for emotion recognition but has some deficiencies that can be overcome with thermal images. Thermal images: a) are less sensitive to lighting conditions, b) have consistent thermal signatures, and c) have a temperature distribution shaped by the branches of facial veins. This work proposes a robust emotion recognition system using thermal images - TERNet. Computer simulations demonstrate an accuracy of 96.2%.

Limitations and future research

We encountered several difficulties due to the biases inherent in analyses of this type. The research has been carried out only in the Web of Science (WOS) database, to limit the amount of work and the size of the article; and we found the Scopus or Google Scholar databases differ quite significantly from those of WoS. In the future, it is desirable to carry out the same study in other databases, with the aim of creating a paper guide as broad as possible that will help researchers to select the articles that are of interest to them and to know the state of knowledge. A comparison of the databases enabled us to extract interesting complementary results.

For an even more exhaustive study, the scope of future bibliometric research should be extended to analyze the content of the “future research” sections of published articles, using text mining.

Competing interests: The authors declare no competing interests.

Añaños-Carrasco, E. (2015). Eyetracker technology in elderly people: How integrated television content is paid attention to and processed. Comunicar, 23(45), 75–83.
Baraybar-Fernández, A. (2017). Evaluación de las respuestas emocionales a la publicidad televisiva a través del neuromarketing. Comunicar, 25 (52), 19–28.
Breninger, B., & Kaltenbacher, T. (2020). Changing Perceptions, Changing Lives–Promoting Intercultural Competence and Ethical Creativity through Advertising. Westminster Papers in Communication and Culture, 15(2).
Camerer, C., Loewenstein, G., & Prelec, D. (2005). Neuroeconomics: How neuroscience can inform economics. Journal of economic Literature, 43(1), 9–64.
Casson A. J. and Trimble E. V. (2018) "Enabling Free Movement EEG Tasks by Eye Fixation and Gyroscope Motion Correction: EEG Effects of Color Priming in Dress Shopping," in IEEE Access, vol. 6, pp. 62975–62987, 2018, doi: 10.1109/ACCESS.2018.2877158.
Casson, A. (2018). Enabling Free Movement EEG Tasks by Eye Fixation and Gyroscope Motion Correction: EEG Effects of Color Priming in Dress Shopping. IEEE Access, 6, 62975–62987.
Clark, K. (2018). How Advertisers Can Keep Mobile Users Engaged and Reduce Video-Ad Blocking Best Practices for Video-Ad Placement and Delivery Based on Consumer Neuroscience Measures. Journal of Advertising Research, 58(3), 311–325.
Clerico, A., Gupta, R., & Falk, T. H. (2015, April). Mutual information between inter-hemispheric EEG spectro-temporal patterns: A new feature for automated affect recognition. In 2015 7th international IEEE/EMBS conference on neural engineering (NER) (pp. 914–917). IEEE.
Cuesta-Cambra, U., Mañas-Viniegra, L., Niño-González, J. I., & Martínez-Martínez, L. (2019). El procesamiento cognitivo de la autorregulación publicitaria de los juegos de azar online en estudiantes universitarios. Revista Mediterránea de Comunicación (10, 2). Doi: 10.14198/MEDCOM2019.10.2.4
Cuesta-Cambra, U., Niño-González, J. I., & Rodríguez-Terceño, J. (2017). The Cognitive Processing of an Educational App with EEG and'Eye Tracking'. Comunicar. Media Education Research Journal, 25(2).
Deza, M., Deza, E., & Vidali, J. (2012). Cones of weighted and partial metrics. In Proceedings Of The International Conference On Algebra 2010: Advances in Algebraic Structures (pp. 177–197).
Doborjeh, Z. G., Doborjeh, M. G., & Kasabov, N. (2018). Attentional bias pattern recognition in spiking neural networks from spatio-temporal EEG data. Cognitive Computation, 10(1), 35–48.
Filipovic, F., Despotovic-Zrakic, M., Radenkovic, B., Jovanic, B., & Živojinovic, L. (2002). An Application of Artificial Intelligence for Detecting Emotions in Neuromarketing. In 2019 International Conference on Artificial Intelligence: Applications and Innovations (IC-AIAI) (pp. 49–494). IEEE.
Golnar-Nik, P., Farashi, S., & Safari, M. S. (2019). The application of EEG power for the prediction and interpretation of consumer decision-making: A neuromarketing study. Physiology & behavior, 207, 90–98.
González-Morales, A. (2020). Right evaluation of marketing stimuli with neuroscience. An electroencephalography experiment. Computers in Human Behavior Reports, 2, 100030.
González-Morales, A., Mitrovic, J., & Garcia, R. C. (2020). Ecological consumer neuroscience for competitive advantage and business or organizational differentiation. European Research on Management and Business Economics, 26(3), 174–180.
Goyal, G. y Singh, J. (2018, abril). Identificación de anotación mínima de los efectos faciales para los anuncios de video. En 2018 International Conference on Intelligent Circuits and Systems (ICICS) (págs. 300–305). IEEE.
Gupta, A., Shreyam, R., Garg, R., & Sayed, T. (2017, August). Correlation of Neuromarketing to Neurology. In IOP Conference Series: Materials Science and Engineering (Vol. 225, No. 1, p. 012129). IOP Publishing.
Gupta, R., & Falk, T. H. (2016). Relevance vector classifier decision fusion and EEG graph-theoretic features for automatic affective state characterization. Neurocomputing, 174, 875–884.
Huang, Y. F., & Kuo, F. Y. (2020). Positive Moods Can Encourage Inertial Decision Making: Evidence from Eye-Tracking Data. In Information Systems and Neuroscience (pp. 229–238). Springer, Cham.
Kang, M. K., Cho, H., Park, H. M., Jun, S. C., & Yoon, K. J. (2017). A wellness platform for stereoscopic 3D video systems using EEG-based visual discomfort evaluation technology. Applied ergonomics, 62, 158–167.
Kaur, R., Gill, R., & Singh, J. (2019, March). Cognitive emotion measures of brain. In 2019 6th International Conference on Computing for Sustainable Global Development (INDIACom) (pp. 290–294). IEEE.
Khushaba, R. N., Wise, C., Kodagoda, S., Louviere, J., Kahn, B. E., & Townsend, C. (2013). Consumer neuroscience: Assessing the brain response to marketing stimuli using electroencephalogram (EEG) and eye tracking. Expert Systems with Applications, 40(9), 3803–3812.
KM, S. K., Rajendran, R., Wan, Q., Panetta, K., & Agaian, S. S. (2019, May). TERNet: A deep learning approach for thermal face emotion recognition. In Mobile Multimedia/Image Processing, Security, and Applications 2019 (Vol. 10993, p. 1099309). International Society for Optics and Photonics.
Lee, N., Broderick, A. J., & Chamberlain, L. (2007). What is ‘neuromarketing’? A discussion and agenda for future research. International journal of psychophysiology, 63(2), 199–204.
Liao, W., Zhang, Y., & Peng, X. (2019). Neurophysiological effect of exposure to gossip on product endorsement and willingness-to-pay. Neuropsychologia, 132, 107123.
Liaudanskaitė, G., Saulytė, G., Jakutavičius, J., Vaičiukynaitė, E., Zailskaitė-Jakštė, L., & Damaševičius, R. (2018, April). Analysis of affective and gender factors in image comprehension of visual advertisement. In Computer Science On-line Conference (pp. 1–11). Springer, Cham.
Libert, A., & Van Hulle, M. M. (2019). Predicting Premature Video Skipping and Viewer Interest from EEG Recordings. Entropy, 21(10), 1014.
Madan, C. R. (2010). Neuromarketing: the next step in market research? Eureka, 1(1), 34–42.
Mañas Viniegra, L., García García, A. L., & Martín Moraleda, I. J. (2020). Audience attention and emotion in news filmed with drones: A neuromarketing research. Media and Communication, 8(3), 123–136.
Mañas-Viniegra, L., González-Villa, I. A., & Llorente-Barroso, C. (2020). The Corporate Purpose of Spanish Listed Companies: Neurocommunication Research Applied to Organizational Intangibles. Frontiers in Psychology, 11.
Monge-Benito, S., Olabarri-Fernández, E., Usin-Enales, S., Etxebarria-Gangoiti, J., Horna-Prat, E., & Mínguez, J. (2019). Advertising directed to bilinguals: do both languages produce the same response? The case of Spanish and basque in basque society. Revista Latina de Comunicación Social, (74), 457–476.
Morillo, L. M. S., García, J. A. A., Gonzalez-Abril, L., & Ramirez, J. O. (2015, April). Advertising liking recognition technique applied to neuromarketing by using low-cost EEG headset. In International Conference on Bioinformatics and Biomedical Engineering (pp. 701–709). Springer, Cham.
Morris, J. D., Klahr, N. J., Shen, F., Villegas, J., Wright, P., He, G., & Liu, Y. (2009). Mapping a multidimensional emotion in response to television commercials. Human brain mapping, 30(3), 789–796.
Murugappan, M., Murugappan, S., & Gerard, C. (2014, March). Wireless EEG signals based neuromarketing system using Fast Fourier Transform (FFT). In 2014 IEEE 10th international colloquium on signal processing and its applications (pp. 25–30). IEEE.
Nemorin, S., & Gandy Jr, O. H. (2017). Exploring neuromarketing and its reliance on remote sensing: Social and ethical concerns. International Journal of Communication, 11, 21.
Ogino, M., & Mitsukura, Y. (2018, September). A Mobile Application for Estimating Emotional Valence Using a Single-Channel EEG Device. In 2018 57th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE) (pp. 1043–1048). IEEE.
Pirouz, D. (2004). The Neuroscience of Consumer Decision-Making.
Plassmann, H., Ambler, T., Braeutigam, S., & Kenning, P. (2007). What can advertisers learn from neuroscience? International Journal of Advertising, 26(2), 151–175.
Pozharliev, R. (2017). Social Consumer Neuroscience: Neurophysiological Measures of Advertising Effectiveness in a Social Context. Journal of Advertising. 46(3), 351–362.
Read, G. (2019). Mates or Married? Implications of Gender Composition and Physical Intimacy on Evaluation of Images Tested for Advertising. Communication Research Reports: CRR, 36(3), 220–230.
Sands, S. F., & Sands, J. A. (2012). Recording brain waves at the supermarket: what can we learn from a shopper's brain? IEEE pulse, 3(3), 34–37.
Shen, F., & Morris, J. D. (2016). Decoding neural responses to emotion in television commercials: an integrative study of self-reporting and fMRI measures. Journal of Advertising Research, 56(2), 193–204.
Stanton, W. J., Etzel, M. J., Walker, B. J., Báez, E. P., & Martínez, J. F. J. D. (2004). Fundamentos de marketing.
Talukdar, D. (2011). “Patterns of research productivity in the business ethics literature: Insights from analyses of bibliometric distributions”. Journal of Business Ethics, Vol. 98, pp. 137–151.
Tanida, H., & Kato, T. (2018, July). Verification of brain activity when watching TV commercials using optical topography. In International Conference on Applied Human Factors and Ergonomics (pp. 76–81). Springer, Cham.
Teo, J., & Chia, J. T. (2018, September). EEG-based excitement detection in immersive environments: An improved deep learning approach. In AIP Conference Proceedings (Vol. 2016, No. 1, p. 020145). AIP Publishing LLC.
Teo, J., Chew, L. H., Chia, J. T., & Mountstephens, J. (2018). Classification of affective states via EEG and deep learning. Int. J. Adv. Comput. Sci. Appl, 9(5), 132–142.
Thammasan, N., Brouwer, A. M., Poel, M., & van Erp, J. (2020). Interpersonal EEG synchrony while listening to a story recorded using consumer-grade EEG devices. In Information Systems and Neuroscience (pp. 253–259). Springer, Cham.
Vecchiato, G. (2014). Una función de densidad máxima electroencefalográfica para detectar la memorización durante la observación de comerciales de televisión. 2014 36ª CONFERENCIA INTERNACIONAL ANUAL DEL IEEE INGENIERÍA EN LA SOCIEDAD DE MEDICINA Y BIOLOGÍA (EMBC), 2014, 6969–6972.
Vecchiato, G., Astolfi, L., De Vico Fallani, F., Toppi, J., Aloise, F., Bez, F., Wei, D., Kong, W., Dai, J., Cincotti, F., Mattia, D., Babiloni, F., 2011. On the Use of EEG or MEG Brain Imaging Tools in Neuromarketing Research. Computational Intelligence and Neuroscience 2011, 1–12. doi:10.1155/2011/643489
Vecchiato, G., Cherubino, P., Maglione, A. G., Ezquierro, M. T. H., Marinozzi, F., Bini, F., … Babiloni, F. (2014). How to measure cerebral correlates of emotions in marketing relevant tasks. Cognitive Computation, 6(4), 856–871.
Vecchiato, G., Fallani, FDV, Astolfi, L., Toppi, J., Cincotti, F., Mattia, D., … y Babiloni, F. (2010). El tema de las comparaciones múltiples univariadas en el contexto del mapeo cerebral neuroeléctrico: una aplicación en un experimento de neuromarketing. Revista de métodos de neurociencia, 191 (2), 283–289.
Vecchiato, G., Kong, W., Giulio Maglione, A., & Wei, D. (2012). Understanding the impact of TV commercials. IEEE pulse, 3(3), 42.
Vecchiato, G., Toppi, J., Astolfi, L., Fallani, F. D. V., Cincotti, F., Mattia, D., … Babiloni, F. (2011). Spectral EEG frontal asymmetries correlate with the experienced pleasantness of TV commercial advertisements. Medical & biological engineering & computing, 49(5), 579–583.
Wang, Y., Chattaraman, V., Kim, H., & Deshpande, G. (2015). Predicting purchase decisions based on spatio-temporal functional MRI features using machine learning. IEEE Transactions on Autonomous Mental Development, 7(3), 248–255.
Wriessnegger, S. C., Hackhofer, D., & Müller-Putz, G. R. (2015, August). Classification of unconscious like/dislike decisions: First results towards a novel application for BCI technology. In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 2331–2334). IEEE.
Yadava, M. (2017). Análisis de señales EEG y su aplicación al neuromarketing. Herramientas y aplicaciones multimedia, 76 (18), 19087–19111.
Yılmaz, B., Korkmaz, S., Arslan, D. B., Güngör, E., & Asyalı, M. H. (2014). Like/dislike analysis using EEG: Determination of most discriminative channels and frequencies. Computer methods and programs in biomedicine, 113(2), 705–713.

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Neuromarketing applied to communication as neurocommunication in WOS: bibliometric reviews and a guide to the first twenty years of the 21st century, from 2001 to 2020

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Abstract

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1. Introduction

2. Materials and methods

2.1 Material

2.2 Methods

3. Results

3.1 Global Results

3.2 Search results by research field

4. Discussion and conclusions

4.1 About the publications

4.2 About the journals

4.3 About the techniques

4.4 About the authors:

5. Brief guide and description of the application articles.

Declarations

References

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