Objective
In today's era, the ever-increasing expansion and penetration of social media into various layers of individual and social life have turned these platforms into one of the critical infrastructures in the business world. Social networks, as one of the prominent manifestations of modern media, have not only transformed the communication landscape but have also exerted a profound and multidimensional impact on entrepreneurial processes. On the one hand, population growth, the relative stability of existing jobs, and shifting customer preferences have drawn the attention of economists and sociologists toward the creation of novel opportunities. On the other hand, media – as reflectors of societal values and norms – can shape public perceptions of entrepreneurship and influence entrepreneurial behavior.
Despite numerous studies on the impact of social networks on entrepreneurial intention or access to resources, there remains a significant research gap regarding the systematic identification of the multiple functions of social networks in the process of opportunity recognition. In particular, a comprehensive conceptual model that simultaneously explains opportunity recognition based on the diverse functions of social networks has been lacking in the domestic literature. Therefore, the present study aims to identify the components of entrepreneurial opportunities and the functions of social networks and to propose a conceptual model in this field. The central research question is: through which functions and by influencing which individual and environmental components do social networks contribute to the recognition of entrepreneurial opportunities?
Within the theoretical framework of the research, social networks are defined as web‑based services that enable users to create a profile, connect with other users, and share content. These networks are composed of individuals or organizations linked through social relationships such as friendship, collaboration, or information exchange. They can assist entrepreneurs in accessing information, financing, market knowledge, moral support, and building social capital.
Regarding entrepreneurial opportunities, the study emphasizes two dominant perspectives: the objective view and the subjective view. In the objective perspective, opportunities are seen as existing phenomena waiting to be discovered, with entrepreneurial alertness playing a key role in their identification. In the subjective perspective, opportunities are created by the entrepreneur through an interactive process with the market. Opportunity recognition is described as the heart of entrepreneurship. Among various models, the creativity‑based model of opportunity recognition by Lumpkin and Bergman – comprising five iterative stages: preparation, incubation, insight, evaluation, and elaboration – has been adopted as the main framework. This model was chosen because of its recursive nature and flexibility in explaining the individual‑level activities of entrepreneurs.
The literature review also reveals that numerous domestic and international studies have confirmed the positive role of social networks in entrepreneurship. However, most of these studies have employed quantitative methods and have not systematically identified the multiple functions of social networks through a qualitative approach. Hence, the present research aims to fill this gap by applying a qualitative content analysis method.
Research Methodology
This study is fundamental in terms of purpose and qualitative in terms of method, specifically using content analysis. The statistical population consists of the existing literature in domestic and international scientific databases. Purposeful sampling was conducted among relevant articles. The databases consulted included domestic sources (such as Noormags, Magiran, the Comprehensive Humanities Portal, and the Academic Jihad Scientific Information Center) and international sources (including ScienceDirect, Scopus, Elsevier, and Emerald).
The data analysis method employed the coding technique in three stages: open, axial, and selective coding. The coding process continued until theoretical saturation was achieved. To enhance the accuracy and systematicity of the analysis, ATLAS.ti specialist software was utilised. This software enabled precise categorisation of concepts, calculation of component frequencies, and visualisation of relationships among categories. Content analysis was chosen because the researcher dealt with documentary data, direct access to live samples was limited, and the coding method allowed for the systematic extraction of components from various texts.
Findings
The findings from the coding process revealed 34 components for social network functions and 39 components for entrepreneurial opportunities. The components of social network functions are presented in a comprehensive table, among which the most frequent functions include: communication (frequency: 40), information sharing (27), interaction (17), information exchange (16), participation (11), as well as marketing, e‑commerce, advertising, customer access, and identity building. Other identified functions include socialisation, problem‑solving, education, job creation, idea generation, information production, and customer relationship management.
Regarding entrepreneurial opportunities, the components were categorised into two dimensions: individual and environmental. The individual dimension (28 components) includes factors such as prior knowledge (frequency: 13), having ideas (6), creativity (5), risk‑taking (4), alertness (4), foresight (4), motivation (4), innovation (4), environmental awareness (4), as well as experience, skill, self‑efficacy, tolerance of ambiguity, decision‑making, leadership, hard work, internal locus of control, and determination. The environmental dimension (11 components) consists of social capital, human capital, cultural capital, economic factors, political factors, social factors, socio‑cultural factors, technology, having a mentor/guide, job satisfaction, and social learning. Finally, a conceptual model was developed illustrating that social network functions, through influencing individual and environmental components, lead to the recognition of entrepreneurial opportunities.
Discussion & Conclusion
The final conclusion emphasises that social networks assist entrepreneurs in recognising business opportunities through interactions and communications with peers, access to information, knowledge sharing, marketing, advertising, and the creation of support networks. By providing a platform for experience exchange, feedback, competitor monitoring, and identification of emerging market needs, social networks play a key role in the entrepreneurial process. Moreover, the diverse functions of these networks – ranging from communicative and informational to financial and educational – can influence both individual characteristics (such as creativity, alertness, motivation, and prior knowledge) and environmental factors (including social, economic, and cultural capital), thereby facilitating entrepreneurial opportunities.
This study, by offering a comprehensive model that simultaneously addresses the multiple functions of social networks and the various dimensions of entrepreneurial opportunities – for the first time in the domestic literature – represents a valuable contribution to enriching the entrepreneurship and media literature.
From a practical standpoint, the following recommendations are made:

Entrepreneurs should utilise social networks beyond mere marketing tools, employing them as platforms for identifying market needs, monitoring competitors, receiving feedback, and conducting professional networking.
Supporting organisations and institutions (technology parks, business incubators, universities) should design training programmes and workshops that optimally leverage social networks for opportunity recognition.
Social network managers should improve user interactions, expand advisory spaces, and facilitate feedback mechanisms to enhance entrepreneurs' ability to benefit from these platforms.

For future research, the following directions are proposed:

Investigating the impact of rapid technological changes in social networks on entrepreneurial opportunities using longitudinal and foresight methodologies.
Designing and employing more dynamic measurement tools, incorporating artificial intelligence and machine learning, to analyse social network functions.
Conducting cross‑national comparative studies to identify economic, cultural, and social differences across various countries.
Testing and validating the proposed conceptual model through quantitative methods such as Structural Equation Modeling (SEM) and Confirmatory Factor Analysis (CFA) to increase external validity and generalisability of the results.