1. Introduction

The 21^st century is regarded as the digital century in which online interaction has become a prevalent issue in human’s daily life. Technology has a great influence on the way people interact with one another. It is important to understand at least the basic issues about online communication as the virtual world expands, especially in looking at how gender affects both language utility and perception. This study aims at identifying the intricacies connected to gender dynamics within the digital communication sphere, and illustrating the interferences that engage in shaping online interactions.

The countless availability of social networks, forums and instant messaging platforms give a chance for a rich variety of language exchange. However, these interactions have no social implications. Gender as a core part of identity plays an important role in how people express themselves and interpret others in virtual spaces. This study illustrates how language is used to fulfill the purpose of how recipients interpret and evaluate language. It hypothesizes that gender affects language use in the visual interactions.

Previous research has highlighted distinct differences in communication styles between men and women, both offline and online. For instance, studies have shown that women tend to use a more collaborative, emotive, and supportive language, whereas men often employ a more assertive, competitive, and informative language. These differences, rooted in socialization processes and cultural norms, have extended into the realm of online interaction, potentially influencing the effectiveness and reception of communication in gendered ways.

Moreover, it has been observed in the previous studies that men and women differ in their offline and online communication styles. For example, according to research findings, women use more collaborative, emotional, and supportive language while men use more assertive, competitive or informative language (Jackson et al., 2001; Johnson, 2011). The diversity in males and females’ perception towards the traditions and norms in the real world is also reflected in the virtual world. Language is used for various implications during online interactions, such as social support, conflict resolution, information sharing, etc. Gender diversity has affected the way people achieve them through various language strategies.

This study aims at deepening the interlocutors’ familiarity with the role of gender in visual communication, and showing how gender affects language use and language perception in online interactions. The ultimate goal is to determine the regularities and tendencies which may be utilized in constructing more inclusive and more efficient ways of interrelations via the Internet. The nature of digital spaces is continuously changing; hence, taking into account the gendered aspects of language are necessary in maintaining equality and respect in online interactions.

This study uses both qualitative and quantitative approaches in the process of data collection. To fulfill this purpose, two different research tools are used in the process of data collections, namely administering a Likert-Scale questionnaire including 20 items, and analyzing 100 instant messages extracted from interactions held in mixed-gender online platforms. The collected data will be helpful to answer these research questions:

1. Do gender differences affect Kurdish interlocutors’ utility of language in online interactions?

2. What are the linguistic elements that differentiate males from females’ online interactions among Kurdish interlocutors?

3. How do cultural norms shape online communication patterns produced by Kurdish males and females?

2. Theoretical Background

The theoretical background consists of two sections. The first section is devoted to the relationship between gender and language illustrating how gender diversity affects the use of language in general. The second section is devoted to the previous studies that examined the influence of gender on the utility of language in online interactions.

2.1 Gender and Language

There is a straight relation between gender and language. Gender differences have a considerable influence on all aspects of language production and perception. They affect the phonological structure, word selection, syntactic structure, interactional strategies and the way of encoding and decoding meaning. According to Mulac and Lundell (1980), information about the gender of speakers is detected in interactions even if they are physically absent. Females rather use indirect strategies (Lakoff, 1973; Tannen, 1990), utilize modal auxiliaries and tag questions more (McMillan et al., 1977). They also use emotional expressions more (Mulac et al., 1990), and give compliments and use politeness strategies more compared to men (Holmes, 1988; Fattah, 2020). Moreover, females usually place more emphasis on enhancing social relationship and solidarity through the use of minimal responses, compliments as well as euphemistic, swearing and taboo expressions in their interactions, whereas males generally focus on maintaining independency and competitiveness through the use of argumentative expressions, report talks, jargons and commands in their interactions (Coates, 2015). However, the context of interactions plays a crucial role in the style of interaction of both males and females. For instance, most males and females employ a different communication style while interacting with a different gender. Bilous and Krauss (1988) found out that gender-related language traits are more observable in the interaction held amongst the interlocutors of the same gender compared to the interaction held amongst interlocutors of mixed gender. Speakers usually try to adapt their language style based on the gender of the recipients.

The diversity in language use is not the matter of using some linguistic elements and strategies and the avoidance of some others, but it is mostly connected with the diversity in the frequency of using certain linguistic elements and language strategies (Fitzpatrick et al., 1995). For instance, it is evident to all linguists that females tend to use ritualized utterances and mitigation strategies more compared to males.

The context in which the interactions occur has a noticeable influence on the way language is used by interlocutors. For instance, the way that interlocutors communicate in a formal register is different from the way they interact in an informal way. The way friends interact in a class is different from the way they interact in a café. The way that interlocutors communicate face-to-face is different from the way they interact visually. Visual interactions, unlike face-to-face interactions, are usually not supported by body language, tone of speaking, feelings, etc. (Holmes, 1988). Thus, the context including the setting, the nature of relationship among interlocutors, the register, the topic of interaction and the nature of medium have all highly contributed in shaping daily interactions. In terms of gender differences with reference to language use, the context also plays a great role in the process of language construction and the employment of language use strategies. According to Communication Accommodation Theory in Coupland et al. (1988) , when an interaction is done between a male and a female, both of them try to do some changes in the selection of words and the strategies they usually adopt in the communication with similar gender.

Previous studies have confirmed that the influence of gender on the utility of language has been comprehensively examined, and they all have asserted that men and women are different in the frequency use of certain linguistic features. However, what still needs a deeper examination is the study of the influence of gender on the use of language in the visual world.

2.2 Gender, Language and Online Interaction

Many studies have confirmed that Computer-mediated communication is different from face-to-face interactions and the findings that are attained from face-to-face interactions are not always applicable to the findings achieved in the analysis of computer-mediated communication, especially in relation to the influence of gender on language use. Alahmadi, et al. (2024) examined 14 videos in a study illustrating the relationship between gender and language in Talks at Google. This study found out that female interlocutors use intensifiers, tag questions and sense of humour more compared to males, whereas male interlocutors use hedges, empty adjectives and super polite forms more. These findings, in the use of some aspects of language, are different from what have been observed in the studies that examined face-to-face interactions. For instance, in the preceding study hedges are more used by males in the Talks at Google platform. However, according to Holmes (1988), hedges are more frequently used by females in daily face-to-face interactions. These differences probably resulted from the chances that online interlocutors had to think, edit and make sure that the interactions represented the interlocutors’ intentions (Walther, 1996). This shift in the style of using language in face-to-face interaction and visual interactions needs to be better and precisely considered.

The type of the medium and the social and educational background of interlocutor salso have a considerable impact on the language use in addition to gender; therefore, it is normal to detect a sort of variety across different studies conducted in regard with the use of language in the visual world. According to Herring (1993), women’s language is recognized by the existence of expressions that represent “attenuated assertions, apologies, explicit justification, questions, personal orientation and support of others”, but regarding female language, Herring (1993) associates “strong assertions, self-promotion, rhetorical questions, authoritative orientation, challenges and humour” to them. Witmer and Katzman (1997) state that female interlocutors more likely use emoticons compared to males in the interactions posted in newsgroups. Waseleski (2006) found out that females use exclamatory expressions to show intimacy more than males do. Moreover, Fox et al. (2007) assert that females’ interactions are more expressive than males’. For Fox et al. (2007), the concept of expressiveness is connected with the utility and the inclusion of the interactional elements, such as emphasis, laughter, emoticons and empty adjectives. Furthermore, Baron (2008) out that females’ interactions are closer to the written interactions, whereas males’ communications are closer to verbal interactions. The above studies confirm that females’ language style is different from males’ language styles in online platforms. However, this study examines the role of gender difference in the online interactions done by Kurdish interlocutors. It is confirmed in the abovementioned studies that context including culture, race, setting play an important role in the influence of gender on language use. Therefore, this study is different from the previous studies in terms of examining the extent to which gender difference is reflected in the interactions made by Kurds in online platforms, and determining the frequency of using certain linguistic elements and language strategies in the language of Kurdish women and men.

3. Methodology

This study uses both qualitative and quantitative approaches in the process of data collection. It is quantitative for administering a structured questionnaire, and for determining the frequency of using certain linguistic elements and language strategies. It is also qualitative for analyzing some randomly selected instant messages in a Telegram public channel chat.

3.1 Participants and Sampling Procedure

The present study included 90 users of a Telegram public chat channel as participants. Forty-seven users are males aged (19 to 54 years) and 43 users are females aged (18 to 48 years). Moreover, the selected messages are also taken from the interactions of these 90 participants.

3.2 Data Collection Tools

The data were collected through the following tools:

3.2.1 A Questionnaire

A Likert–Scale structured questionnaire was administered online to Kurdish interlocutors to investigate the influence of gender on their interactions.

3.2.2 Online Interactions

Analyzing language use patterns, including word choice, sentence structure, and interaction styles and strategies of 100 instant messages randomly selected from three Telegram public chat channels with the consideration of the interlocutors’ gender. Fifty instant messages were extracted from males’ interactions and 50 instant messages from females’ interactions by taking the similarity in the total length of each gender’s interaction into account.

3.3 Model of Analysis

The model in this study for data analysis is an eclectic one as it has been designed and adapted based on the basis of the works conducted by Holmes (1988), Herring (1993), Katzman (1997), Alahmadi et al. (2024), and Waselesk (2006).

Variables	Items	Gender	Responses					Statistical Indicator
Variables	Items	Gender	Strongly Disagree	Disagree	Neutral	Agree	Strongly Agree	Mean	St. deviation	t-value	p-value
Perceptions of Language Use	1. The choice of language is important in your online interactions	M	1	4	11	26	5	3.55	0.880	0.287	0.775
		F	1	4	8	28	2	3.60	0.821	0.287	0.775
	2. The choice of language affects the way others perceive you in online interaction	M	2	5	11	24	5	3.53	0.975	0.524	0.601
		F	1	2	8	31	1	3.63	0.757	0.524	0.601
	3. Kurdish interlocutors use different language styles in online interactions.	M	3	3	11	27	3	3.51	0.953	0.470	0.640
		F	1	3	9	27	3	3.42	0.906	0.470	0.640
	4. Interlocutors identity could be identified base on their online interactions.	M	1	2	13	25	6	3.70	0.832	1.933	0.057
		F	1	5	11	22	4	3.35	0.897	1.933	0.057
Overall Results								3.54	0.763	0.460	0.646

Table 3: Descriptive Statistics of Language Use Perceptions

Variables	Items	Gender	Responses					Statistical Indicator
Variables	Items	Gender	Strongly Disagree	Disagree	Neutral	Agree	Strongly Agree	Mean	St. deviation	t-value	p-value
Perceptions of Gender Influence on Online Interactions	5. Male and female use different language styles in online interaction.	M	2	4	10	25	6	3.62	0.968	0.441	0.660
		F	1	4	8	26	4	3.53	0.797	0.441	0.660
	6. Male and female use different language strategies in online interaction.	M	2	3	9	26	7	3.70	0.954	0.745	0.459
		F	2	2	8	28	3	3.56	0.881	0.745	0.459
	7. Gender influences the choice of words and phrases in online interactions.	M	1	3	12	26	5	3.64	0.845	0.817	0.416
		F	0	0	11	28	4	3.77	0.649	0.817	0.416
	8. Gender influences the level of formality in online interactions.	M	1	8	10	25	3	3.45	0.928	0.284	0.777
		F	0	5	8	30	0	3.40	0.791	0.284	0.777
Overall Results								3.59	0.755	0.223	0.824

Variables	Items	Gender	Responses					Statistical Indicator
Variables	Items	Gender	Strongly Disagree	Disagree	Neutral	Agree	Strongly Agree	Mean	St. deviation	t-value	p-value
Perceptions of Gender and Language Dynamics	9. Cultural norms with respect to gender affect online interactions.	M	2	7	6	29	3	3.51	0.975	2.253	0.027
		F	0	0	9	24	10	3.93	0.768	2.253	0.027
	10. Gender is identified based on the interlocutors’ use of language in online interactions.	M	2	4	9	30	2	3.55	0.880	0.366	0.715
		F	0	2	14	25	2	3.49	0.798	0.366	0.715
	11. Gender has an influence on the responses that interlocutors get in online discussions.	M	0	5	13	29	0	3.51	0.688	0.007	0.995
		F	0	3	12	27	1	3.51	0.703	0.007	0.995
	12. There is a difference in the way men and women are treated in online interactions.	M	0	4	11	28	4	3.68	0.755	0.195	0.845
		F	0	0	14	24	5	3.65	0.686	0.195	0.845
	13. Unlike single-gender online platforms, mixed genders platforms have different dynamics.	M	0	0	11	33	3	3.83	0.524	2.463	0.016
		F	1	5	9	26	2	3.47	0.855	2.463	0.016
	14. Implicit strategies are used in online mixed genders platforms.	M	1	7	10	25	4	3.49	0.930	0.383	0.703
		F	2	0	13	28	0	3.42	0.823	0.383	0.703
	15. Interaction dynamics are changed when the gender construction of an online platform changes.	M	0	0	12	29	6	3.87	0.612	0.271	0.787
		F	0	0	10	27	6	3.84	0.615	0.271	0.787
Overall Results								3.63	0.639	0.152	0.879

Variables	Items	Gender	Responses					Statistical Indicator
	Items	Gender	Strongly Disagree	Disagree	Neutral	Agree	Strongly Agree	Mean	St. deviation	t-value	p-value
	16. I use emoticons frequently.	M	5	25	11	6	0	2.38	0.848	4.881	0.000
	16. I use emoticons frequently.	F	1	6	8	24	4	3.37	1.37	4.881	0.000
	17. I use empty adjectives frequently.	M	2	24	14	7	0	2. 64	0.795	6.570	0.000
	17. I use empty adjectives frequently.	F	0	6	8	29	0	3.62	0.734	6.570	0.000
	18. I use mitigations frequently.	M	2	26	14	5	0	2.56	0.795	6.570	0.000
	18. I use mitigations frequently.	F	0	6	8	29	0	3.62	0.734	6.570	0.000
	19. I use minimal responses frequently.	M	5	28	12	2	0	2.58	1.074	6.352	0.000
	19. I use minimal responses frequently.	F	0	2	10	21	10	3.81	0.741	6.352	0.000
	20. I use humor and sarcasm in mixed-gender groups frequently	M	2	8	12	25	0	3.68	0.810	4.557	0.000
		F	7	19	11	6	0	2.47	0.855	4.557	0.000
Overall Results								3.12	0.761	8.113	0.000

The above table illustrates that the overall mean for the variable Gender and Language Dynamics is 3.12, with a standard deviation of 0.761 and a p-value of 0.000. The p-value is 0.000 and it is smaller than the level of significance 0.05; therefore, the overall p-value result proves that there is a statistically considerable difference between males and females’ responses to all the statements related to Behavioral Preferences in Online Interactions. The mean values for both males’ and females’ responses to the items 16, 17, 18, 19 and 20 are to a large extent different. The mean value of the males’ responses to the Item 16 is 2.38, but for the females is 3.37; for Item 17, the mean value for the males’ responses is 2.64, but for females’ is 3.62; regarding Item 18, the mean value for the males’ responses is 2.56, but for females’ responses is 3.62; concerning Item 18, the mean value of males’ responses is 2.58, but for females’ is 3.81; and finally, the mean value for the male responses’ to the Item 20 is 3.68, but for the female responses’ is 2.47. This diversity of all the items in variable 4 is reflected in the overall p-value 0.000<0.05. These results confirm that there is a statistically significant difference between males and females regarding males and females’ behavioral preferences in online interactions. Males considerably use fewer emoticons, mitigation devices and minimal responses compared to females who considerably use fewer humor and sarcastic statements in mixed-gender online platforms compared to males. Males and females are to a great extent similar in their responses to the items related to their perceptions of language choice in online interactions, perceptions of gender influence on online interactions, perceptions of gender dynamics in online interaction. However, they are considerably different in their behavioral preference in online interactions. Both male and female participants

admit that gender has a noticeable influence on the choice of words, language strategies and their language styles as well as their behavior, degree of formality, revealing their identity, and the interaction dynamics.

4.2 Instant Messages Analysis, Findings and Discussion

The analysis of authentic instant online messages also highly contributes to the confirmation of the results obtained from the data collected via questionnaire and to arrive at the precise role that gender diversity plays an important boundary among reference, sense and meaning: an essence for translating rhetorical expressions in constructing and shaping online interactions. To fulfill this purpose, 100 instant messages were randomly selected from three Telegram public chat channels with the consideration of the interlocutors’ gender. Fifty instant messages were extracted from males’ interactions and 50 instant messages from females’ interactions taking into account the similarity between the total length of males’ interactions and the total length of females’ interactions. The results obtained from the analysis of the employed instant messages are illustrated in Table 8.

Based on the results obtained from the selected instant messages, Table 7 demonstrates that the way that males used language in online interactions is to a large extent different from the way that females used. Males are different in the frequency of using certain linguistic elements and strategies from females. For instance, females used hedge devices, empty adjectives, euphemistic expressions, apologies, justifications, minimal responses and emoticons approximately twice more than males, and they used tag-questions, rhetorical questions, intensifiers and exclamatory expressions three times more. However, males use humor and sarcastic expressions three times more than females. This diversity that has been indicated from instant message analysis confirms all what has been achieved from the questionnaire that gender has a great influence on the selection of words and language use strategies of the interlocutors.

Kurdish society as one of the conservative societies encourages differences between males and females, one of the issues that strongly reflect Kurdish society’s view towards language use is gender diversity. Moreover, in addition to cultural norms, religious rules also boost this diversity in the use of language between Kurdish males and females as the majority of them follow Islamic rules and legislations.

5. Conclusions

The most important concluding points derived from the current study are:

1. Males and females admit that the use language is very important and affects the way that a person perceives somebody else in online interactions.

2. Gender diversity affects all aspects of language including word choice, strategy and style in online interactions.

3. Language plays a considerable role in determining the interlocutors’ identity including gender identity in online interactions.

4. Cultural norms and traditions encourage diversity in the use of language in connection to gender differences and this diversity is also reflected in online interactions.

5. Gender composition of an online group changes has a noticeable influence on interaction dynamics.

6. The frequency of using hedge devices, empty adjectives, euphemistic expressions, apologies, justifications, minimal responses, emoticons, tag-questions, rhetorical questions, intensifiers and exclamatory expressions by females is far more by females compared to males. However, Males use humor and sarcastic expressions far more compared to female.

REFERENCES

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Coates, J., 2015. Women, Men and Language: A Sociolinguistic Account of Gender Differences in Language. Routledge.

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Fitzpatrick, M.A., Mulac, A. & Dindia, K., 1995. Gender-preferential Language Use in Spouse and Stranger Interaction. Journal of Language and Social Psychology, 14(1-2), pp.18-39.

Fox, A.B., Bukatko, D., Hallahan, M. & Crawford, M., 2007. The Medium Makes a Difference: Gender Similarities and Differences in Instant Messaging. Journal of Language and Social Psychology, 26(4), pp.389-397.

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Appendix 1: A Likert-Scale Questionnaire

Demographic Information and Online Interaction Habits

· The Participant’s age: ..........................

· Gender: Male ( ) Female ( )

Notice: Rate the following statements on a scale of 1 to 5:

Variables	No.	Item	Strongly Disagree	Disagree	Neutral	Agree	Strongly Disagree
Perceptions of Language choice in Online Interactions	1	The choice of language is important in your online interactions.
	2	The choice of language affects the way others perceive you in online interaction.
	3	Kurdish interlocutors use different language styles in their online interactions.
	4	Interlocutors’ identity could be identified based on their online interactions.
Gender Influence on Online Interactions	5	Male and female use different language styles in online interaction.
	6	Male and female use different language strategies in online interaction.
	7	Gender influences the choice of words and phrases in online interactions.
	8	Gender influences the level of formality in online interactions.
Gender Dynamics in Online Interaction	9	Cultural norms with respect to gender affect online interactions.
	10	Gender is identified based on the interlocutors’ use of language in online interactions.
	11	Gender has an influence on the responses that interlocutors get in online discussions.
	12	There is a difference in the way men and women are treated in online interactions.
	13	Unlike single-gender online platforms, mixed genders platforms have different dynamics.
	14	Implicit strategies are used in online mixed genders platforms.
	15	Interaction dynamics are changed when the gender composition of an online group changes.
Behavioral Preferences in Online Interactions	16	I use mitigations frequently.
	17	I use empty adjectives frequently
	18	I use emoticons frequently.
	19	I use minimal responses frequently
	20	I use humor and sarcasm in mixed-gender groups frequently.

پوخته:‌

ئەم توێژینەوەیە په‌یوه‌سته‌ به‌ لێكۆڵینه‌وه‌ له‌ کاریگەریی ڕەگەز لەسەر بەکارهێنانی زمانی ئینگلیزی دا لەلایەن ئەو کوردانه‌ی کە زمانی ئینگلیزی لە گفتوگۆ ئۆنلاینەکاندا به‌كارده‌هێنن. ئامانجی ئه‌م توێژینه‌وه‌یه‌ بریتیه‌ له‌ خستنه‌رووی ڕۆڵی زمان لە ناسینەوەی ڕەگەزی گفتوگۆكاراندا ؛ دیاریکردنی کاریگەری بنه‌ما کولتووریه‌كان لە داڕشتنی شێوازەکانی ئاخاوتن له‌ له‌لایه‌ن گفتوگۆكارانی نێر و مێی کورد، دیاریکردنی جیاوازی ڕاده‌ی بەکارهێنانی و توخمە زمانەوانییە بنەڕەتییان له‌ لایه‌ ن هه‌ر یه‌ك له‌ ره‌گه‌زی نێر و مێ دا، ستراتیژی و شێوازەکان کە کارلێکەکانی نێر لە مێین جیا دەکەنەوە’. ئەم توێژینەوەیە شێوازێکی تێکەڵاو (چەندایەتی و چۆنایەتی) لە پرۆسەی شیکاری داتاکان بەکاردەهێنێت. ئه‌م توێژینه‌وه‌یه‌ له‌ جۆری رێبازی چه‌ندایه‌تییه‌ به‌ هۆی ئه‌نجامدانی پرسیارنامەیەک بۆ لێکۆڵینەوە لە دیدگاکانی کوردانی قسه‌كه‌ر به‌ زمانی ئینگلیزی. هەروەها له‌هه‌مانكاتدا ئه‌م توێژینه‌وه‌یه‌ چۆنایەتییە به‌ هۆی شیکردنەوەی ١٠٠ پەیامی خێرا کە لەگفتوگۆكانی نێر و مێ وەرگیراون كه‌ له‌ سێ کەناڵی گشتی تێلێگرامدا بەڕێوەچوون. گرنگترین ئه‌م دوو دەرەنجامە کە ئەم توێژینەوەیە پێیگه‌یشتوه‌ ئەمانەن: جیاوازی ره‌گه‌زی کاریگەری لەسەر هەموو لایەنەکانی زمان هەیە لەوانەش هەڵبژاردنی وشە، ستراتیژی و شێواز لە گفتوگۆ ئۆنلاینەکاندا، راده‌ی بەکارهێنانی رێزده‌ربرینه‌كان، هاوه‌ڵناوی بەتاڵ، دەربڕینی ئیفێمیزم، داواكردنی لێبوردن، پاساوهێنانەوە ، ئیمۆتیکۆن، كلكه‌ پرسیار، پرسیاری ڕه‌وانبێژی، زه‌خنكلردنه‌وه‌ و دەربڕینی سەرسوڕهێنەر لەلایەن مێینەکانەوە زۆر زیاترە بە بەراورد بە نێرەکان. بەڵام نێرەکان زیاتر نوکتە و دەربڕینی گاڵتەجاڕانە بەکاردەهێنن.

كلیله‌ ووشه‌: ڕەگەز، زمان، کارلێکە ئۆنلاینەکان، ده‌ربرینه‌ نه‌ریتییه‌كان، ستراتیژی زمان.

دور الجنس في استخدام اللغة في التفاعلات عبر الإنترنت: الكرد كمتحدثين غير أصليين للغة الإنجليزية

الملخص:

تتناول هذه الدراسة تأثير الجنس على استخدام اللغة الإنجليزية من قبل المتحدثين غير الناطقين بها من الکرد في التفاعلات عبر الإنترنت. تهدف الدراسة إلى تحديد الدور المساهم للغة في تحديد جنس المتفاعلين؛ وتحديد تأثير الأعراف الثقافية في تشكيل أنماط التواصل عبر الإنترنت بين الذكور والإناث الکرد؛ وتحديد تكرار استخدام تلك العناصر اللغوية الأساسية، والستراتيجيات والأساليب التي تميز تواصلات الذكور عن الإناث. تعتمد هذه الدراسة على منهج مختلط (كمي ونوعي) في عملية جمع و تحليل البيانات. الجانب الكمي يتمثل في استخدام استبيان بمقياس ليكرت للتحقيق في وجهات نظر الأكراد كمتحدثين غير ناطقين بالإنجليزية تجاه دور الجنس وتأثيره على التواصلات التي تجري عبر الإنترنت. كما أنها نوعية في تحليل 100 رسالة فورية مستخرجة من تفاعلات الذكور والإناث التي جرت في ثلاث قنوات عامة على تطبيق تيليجرام. النقطتان الأكثر أهمية اللتين توصلت إليهما هذه الدراسة هما: أن التنوع الجنسي يؤثر على جميع جوانب اللغة بما في ذلك اختيار الكلمات، والاستراتيجية والأسلوب في التواصلات عبر الإنترنت؛ وأن تكرار استخدام أدوات التحوط، والصفات الفارغة، والتعبيرات التلطيفية، والاعتذارات، والتبريرات، والاستجابات الحدية، والرموز التعبيرية، والأسئلة التوجيهية، والأسئلة البلاغية، والمكثفات والتعبيرات التعجبية من قبل الإناث يفوق بكثير مقارنة بالذكور. ومع ذلك، يستخدم الذكور الفكاهة والتعبيرات الساخرة أكثر بكثير مقارنة بالإناث.

الكلمات المفتاحية: الجنس، اللغة، التفاعلات عبر الإنترنت، التعابیرالطقسية، استراتيجيات اللغة.

* Corresponding Author.

This is an open access under a CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/)

No.	Variable	Cronbach's Alpha	N. Items	Deleted Items
1	Perceptions of language use	0.889	4	--
2	Gender Influence on online interactions	0.853	4	--
3	Gender and language dynamics	0.924	7	--
4	Interlocutors behavioral preferences	0.833	5	--

The frequency of each element based on gender	Language Elements Frequency
The frequency of each element based on gender	Hedge devices	Empty Adjectives	Tag-question	Rhetorical Questions	Intensifiers	Euphemistic Expressions	Apologies	Assertive Expressions	Exclamatory Expressions	Justifications	Humor and Sarcastic expressions	Minimal Responses	Emoticons
Males	8	11	3	2	5	7	2	4	3	3	7	6	23
Females	19	23	9	7	14	15	5	9	8	7	2	11	41