Effect Of L1 And L2 On Valence And Intensity Of Emotional Words In Bilingual Speakers

Background information

Background information

Human beings use language to express their emotional experience. Emotion words describe a negative or positive feeling, such as happiness or sadness, which differs from other words in that their affective valence is encoded in a semantic representation and the impacts in its processing. Bilingual uses and can speak two languages with nearly equal fluency. Most bilinguals speak a native language (L1) and a second language (L2) fluently. However, studies have indicated differences in valency and intensity of words when bilinguals speak. More importantly, the effect seems more significant on emotional words. Garrison and Schmeichel (2019) define emotional words as words characterized by emotional connotations. For instance, words like lonely, neglect, bless, and elegant, among others, denote specific emotional reactions. Landis (2006) explains that emotion words differ from other words in the lexicon and how such words are processed. For instance, emotional words tend to carry a negative valence like the word sad or positive valence like the word happy, which may trigger distinct cognitive processing styles. Schrauf and Sanchez (2004) explain that positive experiences have a general and less specific cognitive processing style, unlike negative experiences, which pose a straightforward style and more elaborative cognitive processing.

The Bilinguals express their emotions differently depending on the type of language they speak at that time, which indicates that experiences with other languages affect the conceptual representations of emotions among the bilingual speakers (Altarriba & Canary, 2004). therefore, bilingualism affects the processing of emotional words due to cultural variables and memory alterations. Native languages tend to be more emotionally laden than second languages, whereas most bilinguals prefer the native language to express positive emotions in the second language. The second language distances the speaker from the emotional experience. Different languages tend to present different emotional experience.

The effect on valence subsequently affects the meaning and intensity of emotion that the word may perceive. Besides, the study also assesses the intensity of the language on the emotional words in different languages. It refers to the level of feelings the word provokes in first or second languages. Rutter et al. (2019) explain that emotional intensity is a way of experiencing a feeling which may be absorbing like sad words, penetrating by insulting words, enhancing, vivid, commanding, and even complex. The use of emotional words in different languages has varied feelings and experiences. Thus, the study assesses the effect of L1 and L2 on the valence and intensity of emotional words among bilingual speakers.

Communication is vital in our daily life as it facilitates the passing information from one person to another. Besides, effective communication is recommended informal and non-informal gatherings to enhance the acquisition of the message. Thus, the use of emotional words during the communication process is inevitable, and every speaker needs to use such words to enhance the effectiveness of the communication process (Brase& Mani, 2017).  Emotional words tend to have a different impact on monolinguals and bilingual speakers, often unnoticed. There has been a great debate on the impact of emotional words on bilingual speakers. Some argue that such words depict solid emotional responses when spoken and heard in the first language (Hernández et al., 2010). However, due to the rapidly changing world in terms of business, technology, and employment, bilingual speaking is a necessity that every person intending to play a role in the globalization process must use.

Statement of the problem

For instance, English is a global language that all native speakers communicate with other people. Studies indicate that English is one of the most foreign languages installed in the school curriculum to allow learners to develop their knowledge and communication (Low, 2020). As the use rate of foreign languages such as English increases globally, the number of bilingual speakers also increases. The impact of emotional words on emotional memory differs when spoken in first and second languages. Communication is inefficient and poor if the words communicated do not deliver the intended meaning or emotions (Narayan et al., 2018). Therefore, if an emotional word does not provoke the intended emotions in a language, the communication process is ineffective and could lead to more significant risks of making poor decisions. Hence, addressing the impact of these emotional words in native and second languages is a breakthrough in solving issues resulting from poor communication and failure to get the intended meaning. For instance, Chinese and English words tend to have a different emotional impact on positive and negative emotion words, making the two languages appropriate for the studies. Besides, most Chinese speakers communicate in English with other people who are non-Chinese, among other native languages, which the study shall bring an understanding of the intensity of the emotions such words create when used during communications. Therefore, the study is vital for research and interpersonal communication. People may understand what intensity an emotional word can have on people’s memories when used during the communication process (Brase, & Mani, 2017). Therefore, it is vital to determine the influence of these emotional words on syntactic elements in sentences when used in first and second languages. Similarly, the study examines the impact of the emotional words on the intensity of emotions they carriers when heard and spoken in the first and second languages. The findings helped conclude how emotional words affect the intensity of emotions when used by bilingual speakers in the first and second languages.

The main purpose of the study was to examine the effect of emotional words on bilingual speakers by assessing observable differences of the effect of L1 and L2 on the valence and intensity rating of the bilingual speakers.

Does L1 and L2 has any impact on the valence and intensity rating?

Since the study assesses the impact of L1 and L2 on the communication process of bilingual speakers, it is vital in assessing the effectiveness of communication processes in many fields. The study benefits linguistics, researchers, government officials, students, managers, employers, employees, and anyone who uses more than one language to convey their information. To mention a few, the government, through the ministry of education, will realize the importance of equipping schools with relevant resources and introducing foreign languages, especially English which is used universally in aiding the communication process. The study helps them plan well for the teaching of English lessons. At the same time, children are still very young to understand better usage of emotional words in communication rather than learning at an older age when the first language would significantly impact the provocation of positive and negative emotions on the speakers.

Purpose of the study

Secondly, researchers heavily benefit from the study since it focuses on many fields of business, communication, linguistics, and general academic research. They would utilize the data and findings obtained for future research and enhance credibility in their research by using of appropriate words during their interviews with native and foreign-language speakers, gaining better insights of the study. Lastly, students and other speakers will learn how to use emotion works well in presenting the intended meaning, enhancing the effective communication process in their academics, businesses, and workplaces.

People use emotional words in communication depending on the setting. Sometimes they use positive, and other times, they use negative emotional words, which tend to have a different valence, an intensity that affects the emotional memory effects of such individuals. Frequent recalling of the emotional words is associated with more emotional memories than the use of neutral words (Aycicegi-Dinn & Caldwell-Harris, 2009). Bilingual speakers indicate stronger use of emotional phrases in the native languages associated with stronger emotional response than when speaking in the second languages (Ayçiçegi-Dinn, & Caldwell-Harris, 2009). Therefore, presenting emotional words in the first language presents a significant impact on the emotion, memory, and meaning of the words.

Ayçiçegi-Dinn,  & Caldwell-Harris (2009) performed a study on Turkish-English bilinguals speakers. The findings indicate that emotional attributes of words boost memory in both languages but have an intense impact on the first language in deep and shallow processing tasks. Immersion of their participants in an English-speaking environment presents more sidelining memory effects of emotional words due to the monastery of the languages. For instance, the permanent residents of North America have strong memory effects of English emotional words due to their immediate exposure to the language when they were still children, as well as their continued use of the language (Zhang et al., 2021). Therefore, emotional words have varied impacts on the bilingual speakers’ first and second languages due to exposure and usage of such words. Ayçiçegi-Dinn and Caldwell-Harris (2009) explained that those who were initiated to Turkish background tend to have more impact on the emotional memory when speaking the emotional words in the Turkish language. The words had a reduced impact on emotional memories when they spoke in English. Schrauf, & Sanchez (2017) discuss that negative emotion vocabularies tend to have approximately 50% in varied languages than positive and neutral and 30% and 20%. The study indicates that monolingual speakers have a stronger impact on emotional words than bilingual speakers, especially when they speak in their first languages. Chaplin (2015) argues that gender also affects the conceptualization and explosion of emotional words since women tend to have more expansions of positive emotions, which would definitely impact the valence and intensity of the first and second languages.

Ayçiçegi-Dinn and Caldwell-Harris (2009) argue that emotional memory effects are presented when emotional words are recalled and used compared to neutral words. Positive emotion words record good memories like happiness and rewards where people recall good things in their lives, while negative emotion words like dead recall terrible things that happen in a person’s life (Citron et al., 2014). First and second language use tends to bring all these emotions, but discussions on which language beings the intensity of the emotions and language are still occurring. As Ayçiçegi-Dinn and Caldwell-Harris (2009) discuss, speaking emotional words in the first language tend to recall more emotional memories than speaking in the second language. Besides, some studies indicate that only negative emotional words impact emotional memories, but the second language tends to have a more intense on the positive memories. Scott et al. (2020) discussed that valence differs in how people use and control their predicate. In first languages, people tend to use content verbs differently from those spoken in second languages, which could influence the intensity and level of emotions such words create to create.

Research question

Abbassi et al. (2015) explain that emotional words are processed automatically and rapidly in the left hemisphere and involve close attention in the right hemisphere. However, different languages make the emotional word processed in either left or right hemisphere. Abbassi et (2015) conclude that those emotional words processed in the right hemisphere are deeper than those in the left hemisphere. However, Castella (2018) explains that secondary languages use the right hemisphere for positive emotion words and the left hemisphere for negative emotion words. Although most arguments have been revoked on the emotion words in L1 and L2, studies prove that they have a psychological impact on the mental states (Shiota & Dacher, 2005). Lee and Potter (2018) argue that emotional words are used in advertising and marketing places. However, they differ in the construct, but negative emotion words tend to have a deeper insight than the positive ones.

Hoemann, Xu, and Barrett (2019) argue that people remember emotional words better in the first language than in the second language compared to neutral words. However, negative emotional words tend to be highly remembered among those speaking a second language compared to the first language. Similar studies by Ayçiçeg and Harris (2004) indicate that second languages allow the bilinguals to tolerate the annoying mood associated with processing negative emotions words the bilingual speakers. The study indicates that L2 depicts a more profound recall and processing of negative emotional words when compared to L2. Similarly, the findings by Schrauf and Sanchez (2004) also indicate that second language speakers have more emotional words when compared to neutral emotion words among bilingual speakers. However, detailed cognitive processing tends to trigger negative emotions.  

Studies indicate that emotional words describe unspoken assumptions among various psychologists, corresponding to different mental states (Shiota & Keltner, 2005). This explains why they are associated with emotional memories when spoken in a different language (Ferré et al., 2010). Hence, emotional words convey people’s feelings and emotions and can be used without subjective experiencing an emotion. They are associated with non-verbal expressions like prosody, facial expressions, and body language. Ponari et al. (2015) findings indicate that a lexical decision task on matched positive, negative, and neutral words among the highly proficient English speakers with different first language backgrounds presented similar characteristics in processing emotion lance words. Therefore, the age of acquisition, frequency of use, the context of the English, and the L1 background does not affect the processing of emotional words among the English speakers. The effect of emotional words on valence entails the words affecting the type and number of arguments controlled by a predicate in the word.

The Affect-as-information Theory

Ptaszynski et al. (2010) discuss that The Affect-as-Information theory focuses on the interface between emotion and cognition. The theory applies in the study since the emotion words rely between a person’s cognitive abilities and emotion as they raise the emotional memories of different circumstances. According to the theory, affect and mood operate as a source of information. People draw information from their feelings the same way they draw such information from their behaviors (Ptaszynski et al., 2010). In bilingual speakers, inspirational words tend to have a different perception of the information in different languages (Brase & Mani, 2017).

Significance of the study

Schrauf, & Sanchez (2004) use this model to study emotional words by assessing the complex physiological affective and cognitive responses to the physical and sociocultural environment. To the research, positive and negative emotional words have two separate channels of evaluative processing, and language becomes the determining factor in evaluating such words’ intensity (Schrauf, & Sanchez, 2004). Therefore, Affect-as-information Theory explains different emotions presented by inspirational words in the study.

Conceptual framework

Figure 1.1: Conceptual framework

The conceptual framework examines the impacts of L1 and L2 on the valence and intensity rating of the emotional words. The difference is compared when such words are spoken in the first language and second languages. Valence is assessed by the impact of predicate control in a second language which studies indicate to be more intense and provoked more negative memories than when spoken in first languages. Thus, the conceptual framework provides a summary of the variables assessed. 

Communication is a vital aspect of any culture and person in society. However, language is essential to enhance effective communication that builds relationships and increases a sense of community and understanding. Emotion words have been identified to affect individuals’ way of communication, but studies indicate that they differ based on either use of the first language or the second language. Therefore, understanding the effect of the first and second language on bilingual speakers would be appropriate to enhance their memory, critical thinking skills, concentration, listening, and problem-solving skills. This section presents the methodology for the study on the effect of emotional words on bilingual speakers, specifically assessing the impact of L1 and L2 on the valence and intensity rating of the bilingual speakers. 

The study was a quantitative study utilizing a cross-sectional descriptive study design. This study design aims to formulate a problem, develop the working hypothesis, and research and discover insights and ideas on the problem relevant to the study. A cross-sectional descriptive study design systematically and accurately described the phenomenon, situation, and population, answering where what, who, and when questions concerning the phenomenon (Blatch-Jones et al., 2018). However, the study design used various research methods to investigate variables. The descriptive cross-sectional study design involves looking at data from a population at one specific time. It is used to describe the characteristics of a community but not to determine the cause-and-effect relationships between variables (Blatch-Jones et al., 2018). The descriptive study design helped identify the characteristics, trends, categories, and frequencies of events that helped in problem-solving. Therefore, it provides a platform for understanding when, where, and how L1 and L2 affected bilingual speakers’ valence and intensity rating. 

Therefore, the descriptive research design provides reliable and accurate findings predicting the outcome of the transformation describing the potential answer to the research problems by determining how the research topic variables are related. 

According to González-Cabrera, Domínguez-Vidal, and Ayora-Cañada, we can categorize research philosophy into three parts. These include positivism, realism, and interpretivist. Each part of research philosophy covers a wide range of research disciplines (Sefotho, 2015). Besides, some questions cover epistemology, ontology, and axiology methods. Research philosophy is the way used to decide these questions within research. Mostly, the researchers tend to use the positive philosophy. This study adopted realism and positivism philosophical approaches. The research employed a realistic philosophical framework because it creates a picture of real-world perspectives. It was necessary while dealing with English and Chinese language-speaking bilinguals. The research relied on the independent reality of the human mind and the assumptions of science to develop knowledge. Therefore, it presented the ideas concerning the Chinese and English speakers through personal human senses. The positivism philosophy adheres to factual knowledge gained from the senses, measurements, and trustworthiness. Therefore, this philosophy limited the researcher’s role in research in focusing on data collection and interpretation of data, subjectively analyzing the objective. 

Literature Review

The study only targets the Chinese and English bilingual speakers due to the increased availability of Chinese-English speakers for the study. Moreover, studies indicate an increased number of Chinese speakers worldwide, which makes it more appropriate to use the Chinese and English speakers as their first and second language (Zhang & Li, 2010). The target population for the study was managers, supervisors, employees, students, and any other person who was eligible to speak the Chinese and English languages fluently. Determination of the sample size was necessary to obtain the number of participants to participate in the study. The study employed fisher’s formula to calculate the sample size due to its high confidence interval, reduced random error, and high accuracy. 

N = N = Where N is the actual sample size, Z represents the 95% confidence interval, d is the 5% random error, with p representing the population percentage yielding the largest sample size. Therefore, when p is 95%, the sample size was; 

N =

N = 59.697

N=60 respondents

Since the study population is diversified, the researcher used convenience sampling to select the participants, where those who were available during the study were selected to participate in the study. All participants spoke Chinese as the native language and English as the second language. Therefore, the study participants were evenly distributed across the ages and positions, represented equally by gender, and in similar native and second languages. 

The convenience sampling technique is elective, subjective, and judgmental since it relies duly on the researcher’s decision in choosing the subjects to participate in the research (Etikan, Musa & Alkassim, 2016). The method was relevant since it was impossible to determine which participants were available during the data collection. The participants were selected randomly during the study. However, only those participants who could consent and were available for the study were involved. It states the number of respondents the researchers initiate to take up their research. 

Every person within the target range of participants who understood the study topic spoke English and Chinese languages fluently and was able to consent to the study was involved in the study. 

The study included those individuals who had sufficient knowledge of the research question. However, only those above 18 years were able to participate in the study. Therefore, the participants participated in the online survey, providing relevant information on the research question. The participants in the online survey willingly provided the information required for the study. This enhanced the collection of the right result making the study credible and correct. 

All persons who could not speak English and Chinese, could not respond, and give their ideas in any form were excluded from the study. Any person sampled to participate in the study and who was absent was also excluded, and convenience sampling continued until the minimum desired sample size of 60 participants was acquired. Individuals who were below 18 years, sick, and mentally challenged were excluded from the study. This prevented the collecting of unnecessary information and wrong information that would distort the study findings.

The researcher used quantitative methods for data collection. The process involves assessing and analyzing the effects of emotional words on the participants, specifically assessing the impact of the Chinese language as the first language (L1) and the English language (L2) as the second language on the valence and intensity rating. The researcher used online survey questions to obtain information from research participants. The questions asked entailed asking the participants to rate the valence and intensity of a total of 6 groups of emotional words, namely happiness, sadness, fear, surprised, disappointment, and anger, among the sixty Chinese English bilingual participants. The participants were given 72 hours to complete the survey questions and revert through the online platform for the research team for analysis. Besides, we emailed the survey questions in groups of ten to fifteen questions a day to enhance accuracy and get more time to organize the questions received and sent. The quantitative data were analyzed by statistical and mathematical tools allowing generalized conclusions. The results would be used to ascertain the observed difference in the impact of L1 and L2 on the valence and intensity rating. 

The study assessed the six emotion words (anger, happiness, sadness, fear, disgust, and surprise) using one hundred survey questions assessing the effects on valence and intensity ratings. The words were closed into positive and negative emotion words. The study assessed their different influence on the valence and intensity rate in the two languages. The study used a ten-point Likert Scale to rate the variables ranging from zero to 10, where zero represented no impact while ten was the highest rating (Courser & Lavrakas, 2012). The questions entailed assuming the language background and the mean of factors like anger, hate, joyful, afraid, disappointed, afraid, excited, gloat, embarrassment, peaceful, frightened, boring, lonely, good, surprised, annoying, and anxious. The words were presented in both Chinese and English languages assessing the rate of valence and intensity. Language background was assed based on gender, birthplace, age, languages spoken as a child, languages you consider your mother tongue, languages spoken fluently without struggle, and the rate of English and native languages. Assessing these factors in the survey’s question provide quality and enough data on the research question, which the results are analyzed and presented in results sections. 

The online survey questions were reliable and valid because they targeted specific participants and entailed every question regarding the study topic and question which the participants answered. The question was direct to the point, and the researcher provided enough time for the participants to answer them at their own convenient time. Besides, the research dealt with a few online surveys at a time, enhancing accuracy and providing time for clarification of the questions asked by the participants. Ethical considerations were utilized where the participants voluntarily participated in the study and were willing to withdraw at any time, making the data collected more efficient and accurate. Therefore, online surveys as research instruments were reliable and valid.

The research sought permission to carry out the study from the institutional review board. Afterward, the researchers asked the participants to give informed consent for the study. They reminded them that the participation was voluntary and that no one would care for them or penalize them if they withdrew from the study. Moreover, the research informed them that they would stop the research at any time if they were unwilling and insecure to participate. The study allowed the participants to ask questions and any clarifications regarding the research. All information obtained would be kept secure for confidentiality. Also, in the consent form, the confidentiality of their data is ensured (Yip, Han & Sng, 2016). This means that we could not disclose the personal details of the respondents throughout the research. The researcher also ensured that we solely used the data collected from the respondents for this research. The participant information sheet outlined the study’s purpose and background, what the participants were supposed to do, and the general benefits and risks involved. Every participant provided informed consent by signing a consent form before the study began. Reminders of the participants’ involvement being voluntary were emphasized and also reminded of leaving the research process without being asked questions or giving any explanation. During the survey, the participants were reminded not to mention or write their names or any information that would allow identification, including which specific degree they were studying, to ensure we kept confidentiality (Yip, Han & Sng, 2016). The results were kept in a hard-drive and safely kept in a lockable cabinet within the supervisor’s office, and upon transcription, the team erased all the data. Therefore, only research participants who agreed to consider the ethical issues were allowed to participate in the study.

The researcher used Excel and SPSS software to analyze the collected data obtained from the online survey. The researcher used a t-test to compare the means of the emotion words (happiness, sadness, fear, surprised, disappointment, and anger) in English and Chinese. However, to determine the relationship between the research questions and the study problems, the researcher determined regression analysis to find the correlation between the impact of L1 and L2 on the valence and intensity rating of the participants in the six emotion words to conclude the hypothesis. 

This chapter presents data analysis, results, and interpretation. It is done logically using texts, graphs, percentages, numbers, and tables. In summarizing the outcome, the researcher was guided by the general objective to examine the effect of emotional words on bilingual speakers by assessing observable differences in the effect of L1 and L2 on the valence and intensity rating of the bilingual speakers. The researcher then successfully analyzed the data obtained from sixty participants during the online survey. Sixty online survey questionnaires emailed to the participants were returned. The researcher randomly identified other participants in cases where some failed to return the question or were filled based on the inclusion criteria ensuring that the response rate met the minimum sample size of 60 participants. The results of the study are represented and interpreted in this section.

Language Background

Table 4.1: Language Background

	Scale	Frequency (F)	Percent (%)
Gender	Male	26	43.3
	Female	34	56.7
Age	18-25	12	20.0
	26-35	25	41.7
	36-45	16	26.7
	46 and above	7	11.7
Position	Managers	9	15.0
	Employers	14	23.3
	Supervisors	9	15.0
	Students	25	41.7
	Non-Residents	3	5.0
Native Language	Chinese	47	78.3
	English	4	6.7
	Others	9	15.0
Language spoken when child	Chinese	40	66.7
	English	12	20.0
	Others	8	13.3
Frequent Language	First Language (L1)	32	53.3
	Second Language (L2)	13	21.7
	Third Language (L3)	15	25.0
Use of English	Reading	14	23.3
	Writing	18	30.0
	Speaking	19	31.7
	Listening	8	13.3
Use of Native Language	Reading	20	33.3
	Writing	24	40.0
	Speaking	8	13.3
	Listening	8	13.3

Source: (Research Findings, 2022)

The results show that out of 100% (n=60), 56.7% (n=34) of the participants were female and 43.3% (n=26) were male. 41.7% (n=25) were aged 26 to 35 years, 26.7% (n=16) aged 36 to 45 years, 20.0% (n=12) aged 18 to 25 years. 11.7% (n=7) were aged above 45 years. The data from the language background indicates that more females were represented in the study due to increased mastery of the bilingual languages in females. The largest group of the participants were students, represented by 41.7% (n=25), followed by almost half with employers at 23.3% (n=14), then managers and supervisors at 15% (n=9), each with the non-residents being the last by 5% (n=3). 78.3% (n=47) said that Chinese was their native language, 15.0% (n=9) said that other languages were their native languages, with only 6.7% (n=4) indicating that their native language was English. However, as a child, 66.7% (n=40) indicated that they were spoken Chinese when they were children, and 20% (n=12) said that English was the language they were spoken to by their parents, relatives, guardians and grandparents. However, only 13.3% (n=8) said that they were spoken other languages. This indicates that most participants considered Chinese their mother tongue (L1), with very few considering English and other languages. This indicates that English is the second language of most of the participants. 53.3% (n=32) agreed that they speak their first language more frequently, followed by 25.0% (n=15) indicating that the third language was the most spoken in their life. This was closely followed by 21.7% (n=13) who agreed that the second language was the most spoken. Besides, most of the participants indicated their different use of English and Native languages. 31.7% (19) said that they use English for speaking, 30.0% (n=18) for writing, 23.3% (n=14) for reading, and the rest who were represented by 13.3% (n=8) said that they use it for listening. However, 40.0% (n=24) agreed to use their native language for writing, with 33.3% (n=20) using their native language for reading. Only 13.3% (n=8) said they use their native languages to speak and listen. Therefore, the results indicate that many participants use native and English languages for writing and reading, with the majority using English for speaking.

 

Figure 4.1: Graph indicating Gender of the respondents

Figure 4.2: Graph showing Native languages of the participants

 

Figure 4.3: Graph indicating most spoken languages of the participants

For descriptive statistics, a t-test was used to compare the means of the emotion words (happiness, sadness, fear, surprised, disappointment, and anger) in English and Chinese. The data were screened, and only data of those participants who completed the online survey questions on the six emotion words in two languages were selected. The results present the mean of the valence and Intensity of the participants on happiness (H), fears (F), sadness (SD), disgust (D), surprise (S), and anger (A) for English (L2) and Chinese (L1) Languages.

Table 4.2: Mean of Valence and Intensity for Chinese Language (L1)

MEAN (CHIN):	Valence	Intensity
Anger	2.541010101	6.014470588
Happiness	6.314619165	5.971621622
Sadness	3.202997543	5.511302211
Fear	3.460872236	6.217235872
Disgust	2.193319838	6.265306122
Surprise	4.593393393	6.083538084

Source: (Research Findings, 2022)

 

Figure 4.3: Mean of Valence and Intensity for Chinese Language (L1)

The average mean valence for the Chinese Language was 3.839, while the average intensity was 5.533. The negative emotion words tend to lead in the mean on the intensity rate, with disgust leading by an average mean of 6.265, followed by fear with 6.217. Surprise had a mean of 6.084, anger at 6.0145, and happiness at 5.972. sadness recorded the least with 5.511. However, the positive emotion words tend to record a high valence rate, with happiness recording 6.315, followed by surprise with 4.593. Fear, sadness, anger, and disgust recorded a low valence rate, almost the same with 3.461, 3.203, 2.541, and 2.193, respectively. Therefore, the higher intensity rate is recorded among the negative emotion words while the high valence rate is recorded among the positive emotion words for the L1 (Chinese Language).

Table 4.3: Mean of Valence and Intensity for English Language (L2)

MEAN (ENG):	Valence	Intensity
Anger	3.357757758	6.28008008
Happiness	6.405093093	5.182338385
Sadness	3.591877878	4.916332332
Fear	3.532788789	5.830596597
Disgust	4.638438438	6.039039039
Surprise	4.724880383	5.744019139

Source: (Research Findings, 2022)

For the English language (L2), the valence for positive emotion words like happiness was higher than negative words like sadness. The average mean valence for English was 4.275, while the average intensity was 5.527. Happiness recorded an average mean of 6.405 for valence, which is very high than negative words like anger and sadness, which recorded a valence of 3.358 and 3.582. We recorded fear and disgust at 3.533 and 4.638. The surprise was slightly more significant, with an average mean of 4.638. Intensity recorded a slightly low rate of happiness with an average mean of 5.182, with anger having the highest mean of 6.280, disgust at 6.039, fear with 5.831, and sadness with 4.916. Surprise recorded an average mean of 5.744 on the rate of intensity.

Figure 4.4: Mean of Valence and Intensity for English Language (L2)
Table 4.4: Regression Analysis 

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.898a	.806	.573	13.62266
a. Predictors: (Constant), mean_SU_chi_AI, mean_SU_engV, mean_A_chiV, mean_SA_engValence, mean_D_eng_AI, mean_Happiness_Engv, mean_SU_chiV, mean_H_chi_AVI, mean_A_eng_AI, mean_H_engI, mean_SA_chi_AI, mean_F_engV, mean_A_chi_AI, mean_SU_eng_AI, mean_SA_engI, mean_A_engV, mean_H_chiV, mean_SA_chiV, mean_F_chiV, mean_D_engV, mean_D_chiV, mean_D_chi_AI, mean_F_eng_AI, mean_F_chi_AI b. Key: V-Valence, I- Intensity, H-Happiness, A-anger, D-Disgust, SU-Surprise, SA-Sadness and F-Fear.
ANOVAa
Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	15433.041	24	643.043	3.465	.003b
Residual	3711.537	20	185.577
Total	19144.578	44
a. Dependent Variable: L1L2
b. Predictors: (Constant), mean_SU_chi_AI, mean_SU_engV, mean_A_chiV, mean_SA_engValence, mean_D_eng_AI, mean_Happiness_Engv, mean_SU_chiV, mean_H_chi_AVI, mean_A_eng_AI, mean_H_engI, mean_SA_chi_AI, mean_F_engV, mean_A_chi_AI, mean_SU_eng_AI, mean_SA_engI, mean_A_engV, mean_H_chiV, mean_SA_chiV, mean_F_chiV, mean_D_engV, mean_D_chiV, mean_D_chi_AI, mean_F_eng_AI, mean_F_chi_AI

Coefficientsa
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
B	Std. Error	Beta
1	(Constant)	6.078	29.836		.204	.841
mean_Happiness_Engv	3.000	4.139	.166	.725	.477
mean_H_engI	1.716	4.081	.097	.420	.679
mean_D_engV	-1.572	2.348	-.171	-.670	.511
mean_D_eng_AI	-1.878	1.854	-.185	-1.013	.323
mean_A_engV	.836	2.609	.068	.321	.752
mean_A_eng_AI	-1.658	3.101	-.128	-.535	.599
mean_F_engV	3.395	5.019	.178	.676	.506
mean_F_eng_AI	10.102	5.633	.733	1.793	.088
mean_SA_engValence	.033	2.892	.002	.012	.991
mean_SA_engI	.127	3.436	.009	.037	.971
mean_SU_engV	-3.016	2.654	-.220	-1.136	.269
mean_SU_eng_AI	1.854	2.693	.145	.688	.499
mean_H_chiV	4.140	3.849	.249	1.076	.295
mean_H_chi_AVI	-4.506	2.570	-.342	-1.753	.095
mean_D_chiV	4.951	4.029	.403	1.229	.233
mean_D_chi_AI	-8.146	3.179	-.825	-2.562	.019
mean_A_chiV	-3.937	2.690	-.286	-1.464	.159
mean_A_chi_AI	.118	4.078	.009	.029	.977
mean_F_chiV	-4.739	4.089	-.288	-1.159	.260
mean_F_chi_AI	-.655	5.778	-.053	-.113	.911
mean_SA_chiV	4.948	5.720	.286	.865	.397
mean_SA_chi_AI	-2.213	3.255	-.175	-.680	.504
mean_SU_chiV	-1.633	2.757	-.133	-.592	.560
mean_SU_chi_AI	3.357	3.824	.268	.878	.390
a. Dependent Variable: L1L2

Coefficientsa
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
B	Std. Error	Beta
1	(Constant)	6.078	29.836		.204	.841
mean_Happiness_Engv	3.000	4.139	.166	.725	.477
mean_H_engI	1.716	4.081	.097	.420	.679
mean_D_engV	-1.572	2.348	-.171	-.670	.511
mean_D_eng_AI	-1.878	1.854	-.185	-1.013	.323
mean_A_engV	.836	2.609	.068	.321	.752
mean_A_eng_AI	-1.658	3.101	-.128	-.535	.599
mean_F_engV	3.395	5.019	.178	.676	.506
mean_F_eng_AI	10.102	5.633	.733	1.793	.088
mean_SA_engValence	.033	2.892	.002	.012	.991
mean_SA_engI	.127	3.436	.009	.037	.971
mean_SU_engV	-3.016	2.654	-.220	-1.136	.269
mean_SU_eng_AI	1.854	2.693	.145	.688	.499
mean_H_chiV	4.140	3.849	.249	1.076	.295
mean_H_chi_AVI	-4.506	2.570	-.342	-1.753	.095
mean_D_chiV	4.951	4.029	.403	1.229	.233
mean_D_chi_AI	-8.146	3.179	-.825	-2.562	.019
mean_A_chiV	-3.937	2.690	-.286	-1.464	.159
mean_A_chi_AI	.118	4.078	.009	.029	.977
mean_F_chiV	-4.739	4.089	-.288	-1.159	.260
mean_F_chi_AI	-.655	5.778	-.053	-.113	.911
mean_SA_chiV	4.948	5.720	.286	.865	.397
mean_SA_chi_AI	-2.213	3.255	-.175	-.680	.504
mean_SU_chiV	-1.633	2.757	-.133	-.592	.560
mean_SU_chi_AI	3.357	3.824	.268	.878	.390
a. Dependent Variable: L1L2

From the regression analysis, the effects of emotional words (happiness, sadness, fear, surprise, disappointment, and anger) on the valence and intensity of the bilingual speakers indicate a strong positive correlation. The R-value was 0.898, and the R2 (was 0.806). This indicates that the emotional words affect the valence and intensity of bilingual speakers by 80.6%, which is a higher positive significance. The F value was 3.465, and the probability p was 0.003208, which is less than the significance value of 0.05, which indicates a positive correlation of the effect of emotional words on the valence and intensity of bilingual speakers. Therefore, we reject the null hypothesis and accept the alternative hypothesis that there was an observable difference and a significant impact of emotional words emotion words (happiness, sadness, fear, surprised, disappointment, and anger) on the valence and intensity of L1 and L2 languages among the bilingual speakers. Thus, L1 and L2 significantly impact the valence and intensity rating. However, the analysis of the mean of the variables distinguishes positive and negative emotional words that have a different impact on the valence and intensity rating. Despite the positive correlation between the emotion words and the valence and intensity rating in bilingual speakers, the findings indicated that the native language (L1), the first language recorded slightly lower valence rates than the second language throughout the emotion words. See figure 4.5. However, disgust recorded the most significant range between L2 and L1. L2 recorded 4.648, and L1 recorded 2.193. The valence for happiness and surprise is slightly higher in L2 than in L1 but recorded the highest vales. Intensity is high in L1 than in L2. The emotional words in the second language record high valence since the average means for valence in L1 (3.839) is lower than the average valence in L2 (4.275). On the contrary, Intensity in L1 (5.533) was higher than in L2 (5.527), which indicates that emotional words have a higher impact on native languages (Chinese) and first languages than on second languages (English). This justifies the different observable impacts of emotional words on bilingual speakers.  

 

Figure 4.5: Comparison of the valence and intensity rating in English and Chinese

The study findings on assessing the impact of emotional words on bilingual speakers indicate a positive relationship between the impact of different emotional words on valence and intensity of the first and second languages when spoken by bilingual speakers. The impact of predicate control in a second language was more intense and provoked more negative memories than when spoken in first languages. Words such as sadness, disappointment, fear, and anger recorded higher valence in the English language than when spoken in Chinese (see figure 4.5). However, in some cases, like fear and surprise, the difference was more negligible compared to other cases like anger and disgust. This indicates that the second language affects the number and types of arguments controlled by a predicate more than the first language. It affects the connections of syntactic elements in the sentence for negative emotion words, which would distort the meaning of the word. Therefore, by affecting the valence in the second language, the emotional memories recalled would be lower. The difference is compared when such words are spoken in the first language. Positive emotion words like happiness and surprise positively impact valence, which is higher than those in negative words but has almost the same valence in Chinese and English languages (see figure 4.5). Therefore, bilinguals are impacted in control of predicate and syntax elements in positive words but have an almost similar impact in both languages. However, the intensity of the words for recalling negative and positive emotional memories is very high in native languages in negative and positive emotion words than in the second language (see figure 4.5). Therefore, we deduce that bilinguals tend to have more emotional memories when speaking in their native languages than in foreign languages. Moreover, those participants who have spoken the second language while children tend to have less impact of emotional words on their valence and a high impact of such words on the second language. Therefore, it is recommended that teaching the second language to children while young enable the mastery of language, reducing the negative impact of emotional words on their communication.

Bilingual speakers tend to affect the valence and intensity of emotional words when speaking in the first and second languages. It’s because emotional words cause influence people mental states (Shiota & Keltner, 2005). Besides, each emotional word corresponds to a different department store depending on the languages they are spoken in. The mean obtained from the t-tests indicated that emotion words like happiness, sadness, fear, surprise, disappointment, and anger in English and Chinese have different effects on the individuals. The inferential analysis presented a strong positive correlation on the impact of the six emotional words on valence and intensity of the First (L1) and the second (L2) languages commonly spoken by bilinguals. There was a high-intensity rate among the negative emotion words and a high valence rate among the positive emotion words in First languages (L1). The findings indicated that negative emotional words had a major influence on the first language. They recorded high valence and lower intensity in second languages than when spoken in the first language. Indications of the words present the emotional valence of a word with facial expressions (Kauschke et al., 2019). Therefore, speaking reacts to emotions differently depending on the language they speak. From the study, high valence and low intensity of negative words in second languages justify the idea that negative emotional words provoke more negative emotions when spoken in the first language (L1). Megalakaki, Ballenghein, and Baccino (2019) found that valence and intensity affect the comprehension of tests among bilingual speakers in emotional content. The findings indicate that positive and neutral texts score higher emotional valence than negative texts. The results are consistent with our results on using emotional words in the second languages. 

Research on the use of emotional words in advertising has presented emotional and cognitive responses in the contexts of the listeners when the speakers use them in L1 and L2. From the study, Positive emotion words like happiness and surprise positively impact valence, which is higher than those in negative words but has almost the same valence in Chinese and English languages (see figure 4.5). Therefore, while bilingual people speak in the second language, it affects the number and types of arguments controlled by a predicate more than the first language, leading to a lower recall of negative emotional memories than positive emotional memories. The findings indicate that negatively valence words presented a more frowned muscle on the listeners than the positive words, indicating that positive words elicited the orienting responses in listeners compared to negative words (Lee & Potter, 2020). Besides, when positively valence words are used in second languages, encoding information is better than neutral and negative words, consistent with our study findings. 

The intensity of the words for recalling negative and positive emotional memories is much higher in native languages than in negative and positive emotion words in the second language (see figure 4.5). The findings indicated that the mean of the negative words like anger, sadness, disgust, and fear had a very intense rate on those speaking First (L1) languages than those speaking the second (L2) languages. These findings show that bilinguals used more negative emotion words in their preferred languages. Those indicating the most frequently used language indicated that it was their first language associated with more negative emotion words impact valence and intensity (Marian & Kaushanskaya, 2008). Marian and Kaushanskaya (2008) argue that bilinguals’ emotional words are often influenced by the language spoken. Those speaking a first language tend to present a different influence, like depicting more negative words affecting their intensity rates than those speaking a second language. This study presents more bilinguals use emotional words in their native languages (L1), especially for reading, writing, and speaking than in the second language, which is consistent with existing research (Pavlenko, 2005). Studies indicate that medium emotional intensity fosters better compensation of both negative and positive texts, but high emotional intensity benefits positive words more than negative words, which hinders the understanding of the negative words (Megalakaki, Ballenghein & Baccino, 2019). Besides, most participants would recall emotional words more than neutral words, where emotions play a big role in improving information processing. Therefore, we deduce that bilinguals tend to have more emotional memories when speaking in their native languages than in foreign languages.

France, Shah, and Park (1994) discussed that a positive emotion-induced program in advertising enhances the ad promotion, unlike the negative emotions that debates ad evaluation. For instance, linguistics using positive emotion words tends to have lesser effects on television than those using negative emotion words as it brings up emotions. Most people tend to recall critical times, making the ad more effective. Therefore, previous studies have been inconsistent with our study findings indicating that emotional words present a different negative impact on bilingual speakers when spoken in first and second languages. The study findings on the language background present more female participation than male, and most participants were aged above 26 years. Chaplin (2015) discusses small and insignificant gender effects in emotional expressions for adults. However, women seem to have greater emotional expressivity than men. Chaplin (2015) explains that most women express more positive emotions and internalize negative emotions like sadness, which emerges during adulthood. This reflects the intensity of high positive emotions in the study since women were greater than men during the study. 

However, the impact of such emotions in Chinese and English language seemed high, especially in second languages. A large number of participants were students, almost half of the study population that employers followed. This is because the study focused on the participants within the institution and a few others from the surroundings. Students and staff are among the major participants who have excellent experiences in bilingual languages, which made the research limit the study within the school environment, obtaining credible and accurate results. The findings also show that most participants spoke Chinese as their first/native language (L1), appropriate for testing the study variables. Besides, most participants were taught and interacted with Chinese when they were children, making it the most commonly used first language in the study. The participants also speak the first language more frequently because they are used to the language and were born and taught form it since they were children. The two languages are the majority used for writing, speaking, and reading, with listening and scoring the list. 

Conclusion

In conclusion, the valence for positive emotional words like happiness is higher than negative words in second languages. The findings indicate that negative emotion words had a low impact on the intensity of the second language (L2), which affects the connections of syntactic elements in the sentence for negative emotion words. Therefore, by affecting the valence in the second language, the emotional memories recalled would be lower. Bilinguals tend to use different emotional words, which have a different impact on language intensity where the concepts devices form their neutrality. Language intensity among the bilinguals has been majorly affected by their preferred languages. Those preferring first languages experience the influence of negative emotional words on their language intensity. Studies indicate that psychological variables like arousals, cognitive stress, and the need for approval also impact language intensity. The positive emotion words like surprise and happiness recorded a higher impact on valence among those speaking First (L1) languages. Those participants who have spoken the second language while children tend to have less impact of emotional words on their valence and a high impact of such words on the second language. Therefore, bilingual speakers must be more careful while using emotional words in their native and second language to ensure that they present the desired meaning and emotions to the audience, enhancing effective communication. 

The study findings recommend that teaching the second language to children while young enables the mastery of language, reducing the negative impact of emotional words on their communication. Besides, bilinguals need to train more in second languages to ensure that they present the desired message following nonverbal cues to the audience. Future researchers need to examine the effects of emotional words in various communication settings like schools for education, business for product promotion, and general management of various enterprises. Also, future studies need to determine how to minimize the unintended meaning of emotional words in bilingual speaking to provide a better platform for the management and speaking of the message. Lastly, the effectiveness of the communication process through the use of emotional words needs to be examined to identify whether bilinguals present the desired messages when speaking in either language or measures to improve their communication.

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