Social Network Analysis Methods Research Articles

A social network approach to community energy initiative participation

This perspective paper argues how a social network approach can contribute to creating a more comprehensive picture of how individual and community characteristics influence participation in community energy initiatives (CEIs). We argue how social network theory and methods for social network analysis can be utilized to better understand participation. Further, we show how this can potentially aid the implementation of interventions aimed at attracting more participants with more diverse socio-demographic backgrounds. Importantly, we argue that the structure of community social networks connecting (potential) participants could importantly influence whether and how individual and community properties affect CEI participation. Our aim is conveying the social network approach to the field of community energy researchers and stakeholders who might not be familiar with it. We discuss empirical evidence on the effect of network characteristics on CEI participation and the connection between research on CEIs and adjacent fields as a foundation for our claims. We also illustrate how a social network approach might help to overcome biased participation and low participation numbers, by providing social scientists with a tool to give empirically grounded advice to CEIs. We conclude by looking at avenues for future research and discuss how the context of CEIs might yield new theoretical insights and hypotheses.

Analysis on the spatial correlation network and driving factors of carbon emissions in China's logistics industry

Promoting the green development of the logistics industry has become a focal point of attention in China. This study combines an improved gravity model and social network analysis method, focusing on the nineteen provinces of the Yangtze Economic Belt and Yellow River Basin. It constructs a spatial correlation network of carbon emissions in the logistics industry from 2010 to 2021, exploring its formation mechanism and spatial evolution characteristics. The study utilizes a quadratic assignment procedure model to investigate internal driving factors. Building upon this, the study employs an improved STIRPAT model to predict the emission reduction path of the future logistics industry. Results are as follows: (1) Carbon consumption is most pronounced in Shandong, Jiangsu, and Shanghai. The carbon emission shows the characteristics of larger downstream; (2) The bridges of carbon emission-related networks gradually shift from Shandong to Shanxi, Anhui, and Sichuan. Carbon emissions in each sector and spatial spillover effects exhibit dynamic correlations and interactive influences; (3) Energy intensity, freight volume, and the spatial correlation network of the logistics industry are highly correlated; (4) The overall carbon emissions from the logistics industry show a decreasing trend in the future. Anhui and Shaanxi provinces will have high carbon emissions in 2035. The conclusions aim to provide policy suggestions for the region's low-carbon transformation.

Análise de rede sociais de autores e instituições participantes nos anais do WIDAT 2017 a 2023 por coautoria e palavras-chave

The Information, Data and Technology Workshop (WIDaT), with its six editions from 2017 to 2023, published 210 articles in the proceedings with the participation of 395 authors linked to 80 institutions based in 46 cities and 7 countries. The objective of the research is to reveal affinity groups between authors and institutions participating in WIDaT. Qualitative research of an applied nature, used information visualization techniques with the support of social network analysis methods supported by software, such as: OpenRefine, Gephi and Looker Studio. The main result was the analysis of social networks of authors and institutions participating in the six events. The network of authors by co-authorship showed a giant component composed of the majority of authors, while the network of authors by keywords amplified the density of connections, making it a 'small world'. The network of co-authorship institutions revealed strong collaboration between institutions. The network of institutions using keywords identified seven clusters, complemented by keyword clouds, which revealed a semantic cohesion of the topics covered by the institutions belonging to each cluster. Observing the most common keywords for a given cluster can motivate approaches to research collaboration, both for those already consolidated and to strengthen the development of new investigations and studies.

Spatial correlation network structure of carbon emission reduction capacity on urban agglomerations and its driving factors: A perspective of Sustainable Development Goals

Sustainable Development Goal 7 and Goal 13 are important for evaluating carbon emission reduction capacity in urban agglomerations. Exploring the spatial correlation network structures of carbon emission reduction capacity can help synergize carbon reduction actions between cities. Existing research regarding the urban agglomerations to address carbon emission reduction goals has neglected both coordination with Sustainable Development Goals and the impact of spatial correlation network structures. Based on Sustainable Development Goals, an evaluation system of carbon emission reduction capacity is constructed. The characteristics of spatial correlation network structure for carbon emission reduction capacity are described using the social network analysis method. Its driving factors are described using the quadratic assignment procedure method. The Guanzhong Plain urban agglomeration in China is used for validation. The spatial distribution of carbon emission reduction capacity in urban agglomerations is significantly unbalanced, and the spatial correlation network structure follows a stable core-edge pattern. Factors such as differences in technological level, economic level affect the formation of the spatial correlation, but the differences in urbanization level have no significant impact. Countermeasures are proposed to provide a scientific basis for the collaborative management of carbon emission reduction in urban agglomerations.

Academic knowledge brokers in Iran’s health sector: Characteristics, skills, and qualifications

BACKGROUND: Knowledge brokers, as a bridge between producers and users of knowledge, need a set of skills and abilities to fulfill their role. The current study was carried out with the aim of identifying the characteristics, skills, and qualifications needed by knowledge brokers in Iran’s health sector. MATERIALS AND METHODS: This qualitative study was conducted through semi-structured interviews with 18 participants selected using social network analysis and snowball method from June to December 2022. All interviews were analyzed through the conventional content analysis method using the MAXQDA, version 20. RESULTS: Two main categories (personality traits and professional competencies) and six subcategories (extroversion, acceptability, problem-solving skills, interactive skills, specialized skills, and specialized knowledge) were identified for knowledge brokers in Iran’s health sector. Interpersonal communication skills, negotiation and persuasion skills, knowledge in both policymaking and research fields, and marketing and commercialization skills were defined as the most important factors in knowledge brokering. CONCLUSION: Identifying and training qualified and interested individuals to undertake the task of knowledge brokering, by taking into account the characteristics identified in this research and strengthening the required skills and qualifications, can increase the effectiveness of knowledge brokering and help to bridge the gap between research and policymaking.

DIGITAL MARKETING COMMUNICATION STRATEGIES OF COMPANIES TRADING ON SOCIAL MEDIA PLATFORMS

Contemporary trade companies operate within a multifaceted and rapidly changing environment that is shaped by both exogenous and endogenous factors, where digital marketing technologies play a special role. The purpose of the article is to identify the connection between digital marketing technologies and retail business sales regarding their use in marketing budget effectiveness. The study utilized the method of econometric analysis (regression analysis, analysis of descriptive statistics) as well as the method of social network analysis. Regression analysis showed the importance of investment in advertising and customization of marketing campaigns due to the cutting-edge technologies. Factors such as advertising budget, the number of posts, likes, and comments on social networks have a significant impact on sales. Based on the model's findings, every extra dollar allocated towards advertising amplifies sales by 0.0497 units, indicating the importance of investment in advertising campaigns. The sales distribution is somewhat skewed with a mean of 909 and a median of 922. The analysis revealed significant variability in key variables, indicating the diversity of strategies and conditions in which different companies operate. Practical digital marketing solutions for retail businesses include increased investment in social media advertising, regular posts, and engagement through likes and comments. The promising area for further research is to explore the potential of artificial intelligence for personalizing retail business marketing.

An Analysis of Policy Transmission Flow in the Chengdu Plain Urban Agglomeration in Southwest China: Towards Building an Ecological Protection Network

Regional ecological protection is an urgent task in today’s social development, and constructing an ecological protection network is an important way to achieve regional ecological coordination. However, previous studies have lacked a systematic review and analysis of policy document transmission paths, failing to consider the spatial network structure and its complex characteristics of regional ecological protection policies, resulting in deficiencies in regional coordinated governance of the ecological environment. To address this gap, this study constructs an ecological policy transmission network lineage for the Chengdu Plain urban agglomeration (CDPUA) based on 400 ecological environmental protection policy documents issued by cities in the CDPUA from 2015 to 2022, focusing on the transmission perspective of policy documents. Social network analysis methods, a GIS spatial analysis, and other methods were employed to construct the ecological protection network of the CDPUA and analyze the complex spatial structure and characteristics of the network. It was found that the integrated ecological protection network of the CDPUA exhibits a multi-core triangular pattern with spatial characteristics of density in the east and sparsity in the west. The integrated ecological protection network has a density of 60.71%, indicating a strong intercity linkage, with Suining as the central nucleus transmitting policies to surrounding cities, forming the Suining–Chengdu–Mianyang policy transmission triangle. The urban agglomeration has formed an ecological protection network dominated by multiple cities, offering diverse and distinct types of ecosystem services. This study provides insights to enhance regional collaborative ecological governance and protection, promoting sustainable development in the region.

The “Belt and Road” Initiative and China's sporting goods exports: Basic characteristics and policy evaluation

The paper analyzes the basic characteristics of China's sporting goods exports using data from the CEPII BACI database from 2007 to 2019, combined with the social network analysis method, and evaluates the policy effect of the “Belt and Road” initiative implementation on the impact of China's sporting goods exports using the difference-in-differences method. The research findings are as follows: 1) The overall scale of China's sporting goods exports has consistently expanded, marked by a rapid increase in the total export volume. The exported goods exhibit a comprehensive range of product categories, indicating an ongoing evolution in the structural composition of products. Geographically, the export destinations are widespread, covering a diverse range of countries. However, there is a noticeable concentration trend in sporting goods exports, with gymnastics and track and field equipment being the primary export commodities. These sporting goods predominantly penetrate markets in Southeast Asia, West Asia, and Eastern Europe. In the sporting goods trade network associated with the “Belt and Road” initiative, China holds a central role, with Thailand, Turkey, and Poland progressively advancing toward central positions. 2) The implementation of the “Belt and Road” initiative has had a positive impact on China's sporting goods exports, and the policy's influence is particularly significant on the countries and regions along the “Belt and Road”. The implementation of the policy does not favor the breathing growth of sporting goods exports, but it does promote the deepening of the export product. Based on these perspectives, it is imperative for China to establish a robust and sustainable trade network, proactively foster sporting diplomacy, maintain strategic focus, and enhance product quality to effectively propel the development of a sporting powerhouse.

Türkiye in International Energy Trade: Implementation of Social Network Analysis

Energy resources are fundamental inputs in almost every sector and play a crucial role in development and economic stability. This situation has increased the importance of keeping energy costs low, becoming a significant factor in attaining global superiority. In the contemporary era, where states represent the highest level of the organization, the strategic importance of these resources has been further exposed. The strategic value of energy resources, predominantly encompassing fossil fuels such as oil, natural gas, and coal, has precipitated intense global competition. The dynamics of energy resource trade have transcended mere profit-driven motives, transforming into a tool wielded by governments for various political objectives. This paradigm shifts underscores the vitality of energy supply security, prompting the formulation of energy trade networks guided by policies and national strategies. Within these networks, participating actors exhibit diverse traits shaped by distinct circumstances, assuming varied roles through pre-existing relationships. The purpose of the research is to examine the energy trade network of Türkiye, implementing the social network analysis method that integrates empirical data and mathematical approaches. The study aims to unveil pivotal aspects of the network, including its size within the global energy trade landscape, density, relational ties among actors, centrality, and brokerage degrees. The research aims to contribute valuable insights to understanding Türkiye's positioning in the global energy trade through these analyses. The results indicate that the volume of Türkiye's energy trade network accounts for around 1/3 of the global energy trade. While no single dominant actor exists in the network, specific entities demonstrate significant brokerage power. The analysis highlights the impact of global energy players, including Russia, the United States, and some European countries. Finally, the study involves recommendations for future research, anticipating a continued exploration of the complicated dynamics shaping energy trade networks on a global scale.

The global production pattern of the semiconductor industry: an empirical research based on trade network

Semiconductors are an important electronic component and play a central role in many industrial fields, whose production system is spread all over the world, involving trade in many raw materials, mechanical equipment, and finished products. Comprehending a broad global production picture of the semiconductor industry can be an arduous task. To tackle this complexity, the social network analysis method was used to capture the flows of products between economies in the semiconductor industrial chain. This study analyzed the evolution of the trade pattern of four key commodities in the semiconductor industrial chain, with a focus on identifying the status of major economies in the global semiconductor trade system. Additionally, the influencing factors of the formation of the trade networks were explored by using the Exponential Random Graph Model. The results showed that: (1) From 2001 to 2019, the import and export trade pattern of four key commodities in the semiconductor industrial chain has shown the characteristics of “rising in the east and decreasing in the west”, but the change range shows strong commodity heterogeneity, the change of the spatial pattern of integrated circuits trade is the most significant, and the integrated circuits trade proportion of Asian economies has increased hugely with more than 80%. (2) The trade connectivity of various commodities in the semiconductor industrial chain has increased, upstream support products with high technical requirements such as wafers and equipment have the lowest average degree and weak trade liquidity, and the average degree of trade network of packaging materials and integrated circuits is relatively high, with strong trade liquidity and closer and more prosperous trade connections. (3) From 2001 to 2019, the “core-periphery” system of global semiconductor industry trade has changed significantly, with the core circle undergoing obvious iterative reorganization. for example, China and Singapore have achieved status improvement to the core circle in the base materials trade network, while Malaysia has been squeezed into the semi-peripheral circle. (4) The formation of trade networks of various commodities in the semiconductor industrial chain was driven by three aspects: network self-organization, exogenous endowment attribute, and exogenous network embeddedness. Among them, the influence of the technological innovation level of economies on different commodity trade networks showed heterogeneous.

Evaluation of mine ecological environment based on fuzzy hierarchical analysis and grey relational degree

In order to improve the level of mine ecological environment management and restoration, and to improve and enhance the overall environmental quality of mines. This study takes coal mine as the perspective, and constructs evaluation indexes in two steps, i.e., social network analysis method and relevant policy documents are combined to construct evaluation indexes. The indicator system contains 5 first-level indicators and 23 s-level indicators, and the triangular fuzzy number hierarchical analysis method is introduced to determine the comprehensive weight of each evaluation indicator, which overcomes the inadequacy of the objective empowerment method or the subjective empowerment method of single empowerment. The grey correlation analysis theory is used to establish a grey correlation evaluation model of mine ecological environment, which is applied to the evaluation of ecological environmental protection level of four coal mines in a province of China, making full use of the information of each index for quantitative evaluation, and finally obtaining the evaluated value of ecological environmental protection level of each coal mine. It is demonstrated that the evaluation model can make scientific and effective evaluation of the level of ecological environmental protection in mines. The study concludes that coal mines should pay attention to improving the comprehensive utilization rate of coal gangue in the next mine ecological environment management and restoration, and at the same time, reduce the ton of coal power consumption, ton of coal water consumption, and Increase in vegetation cover. This study provides a useful evaluation method for ecological environment management in mining areas, which is helpful to improve the quality of ecological management in mining areas.

From Wesel to Aarau: a case of a community of English emigrants (1555–1558)

The article discusses the issue of the organization of English Protestant migration to continental Europe during the reign of Mary I Tudor. The study is based on the materials of the English immigrant community that formed in Wesel and subsequently settled in Aarau. The aim of the research is to analyze the factors that shaped the course, structure, and nature of English migration, using the Aarau community as a case study. The study is supported by various types of sources, including documents compiled by authorities in Aarau, correspondence between English immigrants and figures of the European evangelical movement, and self-written accounts by the immigrants. The main research methods are methods of social analysis (group analysis, identification of its key parameters) and network analysis (analysis of communication networks). By examining the English immigrant community and the European evangelicals who supported it, the author identifies key individuals who influenced the conditions for emigration. Catherine Willoughby and Richard Bertie played a significant role in the establishment of the community. Thomas Lever, as a community leader, organized the relocation. Heinrich Bullinger and his associates were involved in relations between emigrants and local authorities. Based on the findings of the analysis of the emigration process, the author identified several key factors that contributed to it. These included the social composition of the group (with a predominance of artisans), the religious beliefs of community members, which determined the geography of the migration, inter-сonfessional relations in the area, and active involvement in the organization of migrant movements and accommodation, both by the pastor and prominent figures of the evangelical community.

Research on the coupling test and organizational collaboration relationship between emergency plans and emergency responses—Based on the social network analysis method

Emergency plan is the action guide of emergency response, and the high coupling level and smooth organizational collaboration between emergency plan and emergency response are the necessary conditions for successful response to emergencies. Based on the case of “4–18″ fire accident in Beijing Changfeng Hospital, use social network analysis to quantify and visualize the coupling level and organizational collaboration relationship between emergency plan and emergency response from the overall network and individual central network. The results of the study found that in the overall network, the emergency plan and emergency response organization collaborative relationship network, has a high level of coupling and organizational collaboration. In the individual central network, the network of emergency plan and emergency response organization collaborative relationship has a low level of coupling and organizational collaboration. The results of this study reveal a noteworthy finding that the function of media organizations is unusually prominent in the network of emergency response organization collaboration, while it is not found in the network of emergency plan organization collaboration. As global risks continue to evolve, the results of the study provide valuable insights for other countries and regions seeking to establish emergency plan networks and emergency response networks with high levels of coupling and organizational collaboration, which are essential for enhancing global disaster prevention, mitigation, and response capabilities.

A Study of Quality Management Risks in Construction Projects Based on Social Network Analysis

This research employs a two-dimensional perspective that integrates stakeholders and the entire project lifecycle. It utilizes social network analysis methods and Ucinet6 software to establish a network model of quality management risks in the context of Engineering Inherent Defects Insurance (IDI), Engineering Quality Liability Insurance, and Engineering Quality Assurance Insurance. The study calculates and analyzes the centrality, group density, and cohesive subgroups within the risk network. It identifies key influencing factors and, based on the analysis results, proposes strategies and recommendations. This research provides vital decision support for the future development of the construction industry. The study reveals that three key factors, namely, inadequate construction organization management, unclear construction scope definition, and improper maintenance of construction machinery, are closely related to quality management risk factors. These risks can be effectively mitigated through measures such as strengthening the training of management personnel, implementing relevant regulations, and regular maintenance of construction machinery.

Analysis of the Driving Mechanism of Urban Carbon Emission Correlation Network in Shandong Province Based on TERGM

Analyzing the driving factors and mechanisms of urban carbon emission correlation networks can provide effective carbon reduction decision-making support for Shandong Province and other regions with similar industrial characteristics. Based on industrial carbon emission data from various cities in Shandong Province from 2013 to 2021, the spatial correlation network of carbon emission was established by using a modified gravity model. The characteristics of the network were explored by using the Social Network Analysis (SNA) method, and significant factors affecting the network were identified through Quadratic Assignment Procedure (QAP) correlation analysis and motif analysis. The driving mechanism of the carbon emission correlation network was analyzed by using Temporal Exponential Random Graph Models (TERGMs). The results show that: (1) The spatial correlation network of urban carbon emission in Shandong Province exhibits multi-threaded complex network correlations with a relatively stable structure, overcoming geographical distance limitations. (2) Qingdao, Jinan, and Rizhao have high degree centrality, betweenness centrality, and closeness centrality in the network, with Qingdao and Jinan being relatively central. (3) Shandong Province can be spatially clustered into four regions, each with distinct roles, displaying a certain “neighboring clustering” phenomenon. (4) Endogenous network structures such as Mutual, Ctriple, and Gwesp significantly impact the formation and evolution of the network, while Twopath does not show the expected impact; FDI can promote the generation of carbon emission reception relationships in the spatial correlation network; IR can promote the generation of carbon emission spillover relationships in the spatial correlation network; GS, differences in GDP, differences in EI, and similarities of IR can promote the generation of organic correlations within the network; on the temporal level, the spatial correlation network of urban carbon emission in Shandong Province has shown significant stability during the study period.

Evolution of technology collaboration networks for climate change mitigation and mechanisms for their impacts

The number of patent ap plications for climate change mitigation technologies (CCMT) in China has shown a rapid development trend over the past decade. This study applies social network analysis (SNA) method and directed time-exponential random graph model(TERGM), while considering endogenous network structure variables, node variables and external network covariates, to analyze the Climate Change Mitigation Technology Innovation Cooperation Network (CCMTICN) formed in Chinese provinces, and analyzes the influencing factors and evolution of the CCMTICN from 2011 to 2021 using CCMT patent data from the Himmpat database. The results show that CCMTICN shows obvious core-edge structural characteristics; endogenous network structural variables have a non-negligible influence on the formation of the network, and other factors such as the information exchange network, industrialization level, knowledge level, and the degree of governmental intervention can promote the formation of CCMTICN; whereas, foreign direct investment, urbanization level, and carbon dioxide(CO2) emissions can inhibit the formation of CCMTICN. When considering the 11-year time effect of CCMTICN, it is found that the CCMT cooperative relationship between provinces remains relatively stable.

Penerapan dan Analisis Metode Social Network Analysis untuk Menentukan Rekomendasi Diskon dengan Menggunakan Library NetworkX

At present technology has developed rapidly, especially in industrial technology. Business competition is getting tighter, making people have to find ways to maintain their business. One strategy that can be used is to provide discounts on goods or services sold. This discount can be made based on the company's sales data or other factors. In this case, the company has large sales data. Therefore, a way is needed to process the large sales data, and one efficient way to do this is to use the Social Network Analysis method. This study measures the degree of Information Centrality from the Social Network Analysis method to measure how much the item is purchased, this can be taken into consideration to determine discounts on goods or services sold. This research provides the results of discount recommendation applications that can process large sales data and provide recommendations based on the Social Network Analysis method.

Toward dual carbon targets: Spatial correlation on comprehensive carbon emission index in urban agglomerations based on a new evaluation model

China is confronted with substantial pressure to mitigate its carbon emissions. Urban agglomerations assume a pivotal role in the attainment of carbon peaking and carbon neutrality. This study constructed a carbon emission evaluation model from the perspectives of total quantity, intensity, efficiency, population, and land. A modified gravity model and social network analysis method was used to analyze the spatial correlation characteristics of six urban agglomerations, clarified their carbon emission spillover effects, and explored their influencing factors using the quadratic assignment procedure method. The results are as follows. (1) The carbon emission correlations in the Yangtze River Delta, Pearl River Delta, and Chengdu-Chongqing urban agglomerations increased, while Beijing-Tianjin-Hebei, Central Plains, and Middle Reaches of Yangtze River urban agglomerations decreased. (2) From a macro perspective, the Yangtze River Delta and Pearl River Delta urban agglomerations were at the core of the network, and the “bridging” role of the Middle Reaches of Yangtze River urban agglomeration was evident. From a micro perspective, the cities in the middle of urban agglomerations were more likely to become network cores. (3) Spillover effects between plates were present in the correlation network, with a gradual balance between the reception and spillover relationships. Most urban agglomerations exhibited an uneven distribution of community correlation capacity. (4) Geographic adjacency and urbanization level significantly promoted carbon emission correlation, although the direction and magnitude of other factors’ influence varied. The findings contribute to the implementation of low-carbon planning, carbon reduction strategies and regional sustainable development.

A system dynamics approach for sustainable groundwater management considering climate change, inter-organizational relationships, and domestic water saving

This article uses system dynamic modeling to examine the relationship between water allocation from the Ilam dam and groundwater fluctuation, as well as the effects of climate change, changes in inter-organizational relationships, and water demand management on water allocation and groundwater level fluctuations. The results showed that agricultural water allocation has a direct effect on groundwater level fluctuations. In the first scenario, which examined the effects of climate change, the comparison of three climate change scenarios (SSP126, SSP245, and SSP585) was carried out. The results illustrated that with temperature increasing and precipitation decreasing occurred in SSP585, the groundwater drawdown increases about 0.8 m more than SSP126. The second scenario examined the effects of changes in inter-organizational relationships. Based on the results of centrality measures in the social network analysis method, it was found that the organizational power of the stakeholder organization in the agriculture sector is greater than the ones in the environment sector. This causes the allocation to the agriculture sector to be prioritized over the environment. This scenario was analyzed by assuming a change in organizational power and giving priority to the water allocation of the environmental sector. The results showed that environmental needs (maximum 0.3 MCM) were almost entirely met in the second scenario, compared to the basic scenario. Also, the decrease in agricultural water allocation has led to an increase in groundwater usage by farmers, resulting in a 20 cm drop in groundwater levels. Therefore, regarding the sustainable management of water resources, directing attention towards alternative livelihoods for farmers can contribute to environmental water rights and the remediation of aquifers. The third scenario examined the effects of water demand management. The results showed that saving 20–25% of water in the domestic sector can reduce 40–50 cm maximum groundwater drawdown which align with sustainable groundwater management.

Investigating peer recognition across an introductory physics sequence: Do first impressions last?

Students’ beliefs about the extent to which meaningful others, including their peers, recognize them as a strong science student are correlated with their persistence in science courses and careers. Yet, prior work has found a gender bias in peer recognition, in which student nominations of strong peers disproportionately favor men over women, in some instructional science contexts. Researchers have hypothesized that such a gender bias diminishes over time, as determined by students’ academic year: studies have found a gender bias in peer recognition in science courses aimed at first-year students, but not in science courses aimed at beyond first-year students. This hypothesis that patterns of peer recognition change over time, however, has yet to be tested with longitudinal data—previous studies only examine snapshots of different students in different science courses. In this study, we isolate the effect of time on peer recognition by analyzing student nominations of strong peers across a two-semester introductory physics course sequence, containing the same set of students and the same instructor in both semesters, at a mostly women institution. Using a combination of social network analysis and qualitative methods, we find that while many students receive similar levels of peer recognition over time, the four most highly nominated students—the recognition celebrities—exhibit some change between semesters even in this highly controlled setting. Furthermore, we observe that these changes in the celebrities track closely with changes in student outspokenness and that being outspoken is likely more important for gaining recognition than earning a high grade in the class. These findings lend support to prior work’s hypothesis that peer recognition changes over time, but also challenge the generalizability of previous results (i.e., that patterns of recognition are related to students’ academic year). Instead, peer recognition seems highly sensitive to variables such as individual students’ participation and, therefore, may be course specific. We provide recommendations for both when and how instructors may intervene on peer recognition based on our results. Published by the American Physical Society 2024