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Phase-Synchronized Fluidic Oscillator Pair
(AMER INST AERONAUTICS ASTRONAUTICS, 1801 ALEXANDER BELL DRIVE, STE 500, RESTON, VA 22091-4344 USA, 2019) Tomac, Mehmet N; Gregory, James W.
The relative phase of oscillating jets from a pair of fluidic oscillators was synchronized in this work. The means for this synchronization was mutual interaction through a shared feedback channel between the two oscillators. Flow visualization and hot-wire measurements indicated a strong correlation and phase synchronization between the two oscillators. A numerical analysis offered better understanding of the internal flow physics that led to the synchronization phenomenon. A portion of the output jet from one fluidic oscillator was redirected and crossed over into the adjacent oscillator, leading to momentum transfer between the two oscillators. A portion of this cross-oscillator flow was directed into the shared feedback channel and constituted the main feedback flow. In this process, one of the shared feedback channel outlets was blocked by a vortex, allowing only one oscillator to receive feedback flow. The primary mechanism for in-phase synchronization was the cross-oscillator flow, which was divided into phase-modulated momentum injection to the primary jet and modulated flow input to the shared channel feedback channel.
Citation - WoS: 26
Citation - Scopus: 32
Gigification, Job Engagement and Satisfaction: The Moderating Role of AI Enabled System Automation in Operations Management
(Taylor & Francis Ltd, 2021) Braganza, Ashley; Chen, Weifeng; Canhoto, Ana; Sap, Serap
Innovative and highly efficient Artificial Intelligence System Automation (AI-SA) is reshaping jobs and the nature of work throughout supply chain and operations management. It can have one of three effects on existing jobs: no effect, eliminate whole jobs, or eliminate those parts of a job that are automated. This paper focuses on the jobs that remain after the effects of AI-SA, albeit with alterations. We use the term Gigification to describe these jobs, as we posit that the jobs that remain share characteristics of gig work. Our study examines the relationship between Gigification, job engagement and job satisfaction. We develop a theoretical framework to examine the impact of system automation on job satisfaction and job engagement, which we test via 232 survey responses. Our findings show that, while Gigification increases job satisfaction and engagement, AI-SA weakens the positive impact of Gigification on these important worker outcomes. We posit that, over time, the effects of AI-SA on workers is that full-time, permanent jobs will give way to gigified jobs. For future research, we suggest further theory development and testing of the Gigification of operations and supply chain work.
A Novel Signaling Pathway That Governs Tumor Metastasis: Ceramide Regulates Direct Crosstalk Between TGF-Β and Sonic Hedgehog Signaling
(Wiley-Blackwell, 2016) Gencer, S.; Ogretmen, B.
Ceramide is a key factor that regulates the crosstalk between TGF-beta and sonic hedgehog signaling at the basal cilia to control cell migration and tumor metastasis
(ELSEVIER SCI LTDTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND, 2016) Gencer, Salih; Ogretmen, Besim
Ceramide is a key factor that regulates the crosstalk between TGF-beta and sonic hedgehog signaling at the basal cilia to control cell migration and tumor metastasis
Structure Health Monitoring Using Wireless Sensor Networks on Structural Elements (vol 82, pg 68, 2019)
(ELSEVIER, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS, 2020) Ayyildiz, Cem; Erdem, H. Emre; Dirikgil, Tamer; Dugenci, Oguz; Kocak, Taskin; Altun, Fatih; Gungor, V. Cagri
This paper presents a system that monitors the health of structural elements in Reinforced Concrete (RC), concrete elements and/or masonry buildings and warn the authorities in case of physical damage formation. Such rapid and reliable detection of impairments enables the development of better risk management strategies to prevent casualties in case of earthquake and floods. Piezoelectric (PZT) sensors with lead zirconate titanate material are the preferred sensor type for fracture detection. The developed sensor mote hardware triggers the PZT sensors and collects the responses they gather from the structural elements. It also sends the collected data to a data center for further processing and analysis in an energy-efficient manner utilizing low-power wireless communication technologies. The access and the analysis of the collected data can be remotely performed via a web interface. Performance results show that the fractures serious enough to cause structural problems can be successfully detected with the developed system.
Ceramide Is a Key Factor That Regulates the Crosstalk Between TGF-Β and Sonic Hedgehog Signaling at the Basal Cilia to Control Cell Migration and Tumor Metastasis
(Elsevier Sci Ltd, 2016) Gencer, S.; Ogretmen, B.
Citation - WoS: 6
Citation - Scopus: 6
Experimental Measurements of Some Thermophysical Properties of Solid CdSb Intermetallic in the Sn-Cd Ternary Alloy
(Springer, 2016) Ozturk, Esra; Aksoz, Sezen; Altintas, Yemliha; Keslioglu, Kazum; Marasli, Necmettin
The equilibrated grain boundary groove shapes of solid CdSb in equilibrium with Sn-Cd-Sb eutectic liquid were observed from a quenched sample by using a radial heat flow apparatus. The Gibbs-Thomson coefficient, solid-liquid interfacial energy and grain boundary energy of the solid CdSb intermetallic were determined from the observed grain boundary groove shapes. The thermal conductivity of the eutectic solid and the thermal conductivity ratio of eutectic liquid to the eutectic solid in the Sn-35.8 at.%Cd-6.71 at.%Sb eutectic alloy at its eutectic melting temperature were also measured with a radial heat flow apparatus and a Bridgman-type growth apparatus, respectively.
Citation - WoS: 54
Citation - Scopus: 58
Understanding the Effects of Artificial Intelligence on Energy Transition: The Moderating Role of Paris Agreement
(Elsevier, 2024) Chishti, Muhammad Zubair; Xia, Xiqiang; Dogan, Eyup
This study contributes to the existing literature by investigating and confirming a range of diverse outcomes related to the interplay of factors shaping the global energy transition (ET). Employing advanced methodologies, including the extension of the QVAR technique to short-term (SR), medium-term (MR), and long-term (LR) connectedness analysis, as well as the application of the CQ method to explore relationships within varying market conditions and timeframes, the study examines the interconnectedness of critical variables: artificial intelligence (AI), the Belt and Road Initiative (BRI), the Paris Agreement (PA), green technologies (GT), geopolitical risk (GPR), and ET. The findings highlight several crucial insights. Firstly, all selected variables demonstrate substantial interconnectedness across different time horizons, except for MR, which exhibits comparatively weaker connectedness than SR and LR. Secondly, independent series reveal diverse impacts on ET across various market conditions and periods. For example, in SR, most series produce mixed effects on ET, with BRI having primarily adverse consequences and GPR predominantly yielding positive impacts. In MR, the influence of AI, PA, and GT on ET varies, while BRI enhances ET, and GPR essentially hampers it. Notably, in LR, AI, BRI, PA, and GT significantly promote ET, while GPR disrupts its progress. Additionally, the study underscores the dynamic and time-varying nature of the relationships between AI, BRI, PA, GT, GPR, and ET across different market conditions, thus holding essential implications for shaping global policies to foster sustainable energy transitions.
TGF-Β Receptor I/II Signaling at Primary Cilia Membrane Is Regulated by Ceramide to Modulate Cell Migration
(Elsevier Sci Ltd, 2016) Gencer, S.; Ogretmen, B.
Citation - WoS: 251
Citation - Scopus: 263
Surface-Enhanced Raman Spectroscopy (SERS): An Adventure from Plasmonic Metals to Organic Semiconductors as SERS Platforms
(Royal Soc Chemistry, 2018) Demirel, Gokhan; Usta, Hakan; Yilmaz, Mehmet; Celik, Merve; Alidagi, Husniye Ardic; Buyukserin, Fatih; Demirel, Gokhan; Usta, Hakan; Yilmaz, Mehmet; Celik, Merve; Alidagi, Husniye Ardic; Buyukserin, Fatih
The quantitative determination and identification of bio-/chemical molecules at ultra-low concentrations is a hot topic in several fields including medical diagnostics, environmental science, and homeland security. Molecular detection techniques are conventionally based on optical, electrochemical, electronic, or gravimetric methodologies. Among these methods, surface-enhanced Raman spectroscopy (SERS) is considered as one of the most reliable, sensitive and selective techniques for non-destructive molecular analysis through the amplification of electromagnetic fields and/or creation of charge-transfer states between the chemisorbed analyte molecule and SERS active platform. Unfortunately, the applicability of SERS is rather limited, which is mainly due to the lack of highly sensitive SERS platforms with good stability and reproducibility. In line with this, metal nanoparticles (e.g., Au, Ag, and Cu) have been extensively exploited as SERS active platforms. Although the utilization of metallic nanoparticles in SERS is simple and cost-effective, the poor controllability of the structures and limited formation of hot spots in the detection zone leads to discrepancy in the resulting SERS signals. For these reasons, in the past few years, researchers have focused on fabricating 3-dimensional (3D) SERS platforms, which increase the adsorption of analyte molecules and facilitate hot spot formation in all three dimensions. However, the fabrication of 3D SERS platforms is mostly expensive and technologically demanding. Therefore, the discovery of non-metal alternative approaches is of great interest not only to widen SERS applications but to further elucidate fundamental questions. Considering recent developments on the fabrication and application of SERS active platforms, this review is structured in 3 main directions; (1) implementation of the plasmonic nanoparticles having different shapes into SERS-active platforms, (2) highlighting recent developments in the fabrication and application of 3D SERS-active platforms, and (3) examination of recent novel inorganic and organic semiconductor based platforms for SERS applications. At the end, we conclude with the promises and challenges for the future evolution of SERS.
Citation - WoS: 6
Citation - Scopus: 18
Is Leverage a Substitute or Outcome for Governance? Evidence From Financial Crises
(Emerald Group Publishing Ltd, 2021) Tekin, Hasan; Polat, Ali Yavuz
Purpose The authors investigate the impact of governance on the leverage of East Asian firms in the financial crisis context, in order to understand the puzzle whether debt acts as a substitute for governance or an outcome of the governance mechanism. Design/methodology/approach The authors use 86,030 firm-years and the country-level governance data from eight East Asian countries over the period 1996-2017. The authors employ the fixed effects (FE) model, in the main analysis and the weighted least squares model, as a robustness check in order to compare the two competing hypotheses of agency theory, substitute and outcome models. Findings The authors' results show that debt acts as a substitute for governance before the GFC, but during and after the GFC the picture changes. Namely, debt acts as an outcome of the governance mechanism during the GFC and its aftermath. Since during financial downturns both agency costs increase, and information asymmetry widens, firms in poor-governed countries may be reluctant to increase their leverage in order not to face financial distress and additional restrictions. Thus, the results imply that the use of debt as a tool to mitigate agency conflicts and a substitute for governance strongly depends on the environment that the firms operate and the general macroeconomic conditions, such as facing a financial crisis or not. Research limitations/implications This study provides an interesting case of the firms' capacity to raise money during a crisis and that governance plays an important role in borrowing activities of firms. This will undoubtedly help motivating owners and policymakers for improving governance. The authors' findings may be useful for policymakers to develop policies considering the adverse effects caused by exogenous shocks. This is crucial because the severity of GFC as a shock seems to change the macro and institutional environment that firms operate. While the authors properly address the research hypotheses using country governance data, future research may employ corporate governance data to attain firm-level results by testing two competing hypotheses. Originality/value There are several important areas where this study makes original contributions. First, while Tsoy and Heshmati (2019) focus on the dynamics of capital structure for only Korean firms, the authors extend the sample including eight East Asian countries considering the impact of country governance on capital structure policy. Specifically, this study is the first in using the robust country governance data, which differs by country and year, in the crisis context. Next, the authors investigate both the AFC and GFC to compare whether these two crises have different effects on capital structure policy of East Asian firms. Finally, the authors aim to understand whether leverage is used as a substitute for governance or an outcome of governance mechanism considering recessions.
Citation - WoS: 15
Citation - Scopus: 16
Stacking Ensemble Learning-Based Wireless Sensor Network Deployment Parameter Estimation
(Springer Heidelberg, 2023) Akbas, Ayhan; Buyrukoglu, Selim
In wireless sensor network projects, it is generally desired to cover the area to be monitored at a given cost and to achieve the maximum useful network lifetime. In the deployment of the wireless sensors, it is necessary to know in advance how many sensor nodes will be required, how much the distance between the nodes should be, etc., or what the transmit power level should be, etc. depending on the channel parameters of the area. This necessitates accurate calculation of variables such as maximum network lifetime, communication channel parameters, number of nodes to be used, and distance between nodes. As numbers reach to the order of hundreds, calculation tends to a NP hard problem to solve. At this point, we employed both single-based and stacked ensemble-based machine learning models to speed up the parameter estimations with highly accurate outcomes. Adaboost was superior over other models (Elastic Net, SVR) in single-based models. Stacked ensemble models achieved best results for the WSN parameter prediction compared to single-based models.
Citation - WoS: 11
Citation - Scopus: 11
Biogas Intake Pressure and Port Air Swirl Optimization to Enhance the Diesel RCCI Engine Characteristics for Low Environmental Emissions
(Elsevier, 2024) Dalha, Ibrahim B.; Koca, Kemal; Said, Mior A.; Rafindadi, Aminu D.
Exhaust emission and combustion control in RCCI (reactivity-controlled compression ignition) focused mainly on the direct-injected fuel parameters, urging to investigate the advantages of port-fuel intake parameters. The engine was modified for port injection of Biogas at the valve and RCCI mode. The influence of port swirl ratio (PSR, 0 - 80%) and biogas injection pressure (BIP, 1 - 4 bar) on the diesel RCCI combustion and emissions was tested and optimized at varied loads and 1600 rpm in a port injection at the valve (PIVE) approach. Established kinetic mechanisms were combined with multi-objective optimization to further investigate, predict, and analyze emissions occurrence and trade-offs for reduced environmental impacts. The results show that the radiation absorption triggered by increased CO2 lowers combustion temperature, resulting in prolonged ignition. Setting the airflow to swirl lowers the in-cylinder pressure at elevated BIP while raising the heat generated across the BIPs. Increasing the PSR slows the combustion while BIP speeds up the process. BIP and PSR show great trade-off reduction ability among all emission parameters. The optimum unburned hydrocarbon, nitrogen oxide, particulate, and carbon monoxide emissions for the injection at the valve were found to be 109.58, 0.577, and 2.336 ppm, and 0.103%, respectively, at low-load, low-BIP, and high-PSR. The emissions were lowered by 6.58, 91.26, 80.65, and 13.45% compared to the premixed RCCI mode, respectively. Therefore, introducing lowpressure biogas amid high swirling air at the valve elevates the in-cylinder condition while lowering the emissions, mitigating their environmental implications.
Citation - WoS: 50
Citation - Scopus: 61
Are Clean Energy and Carbon Emission Allowances Caused by Bitcoin? A Novel Time-Varying Method
(Elsevier Sci Ltd, 2022) Dogan, Eyup; Majeed, Muhammad Tariq; Luni, Tania
The bitcoin market has substantially grown in recent years. The researchers are exploring its various repercussions for socioeconomic and political matters; however, the literature still lacks clear evidence on how bitcoin interacts with energy and the environment. This study aims to explore the causal relationship between bitcoin, clean energy, and carbon emissions allowances by applying the novel time-varying Granger causality test on the daily data spanning from Sept 17, 2014, to October 12, 2021. The empirical findings confirm that both clean energy and emission allowances are causally associated with bitcoin. However, this causal relationship varies over time and the duration of causality is longer as suggested by the recursive evolving procedure. The outcome is robust when bitcoin is measured by the volume and the price. Furthermore, the results obtained from robustness analysis conducted through heteroskedastic consistent test also validate the findings that bitcoin causes clean energy and carbon allowance. The findings offer a platform for government officials and policy managers to improve clean energy and carbon allowance markets for sustainable development by managing and using the tools to control and regulate cryptocurrency markets.
Citation - WoS: 5
Node-Level Error Control Strategies for Prolonging the Lifetime of Wireless Sensor Networks
(IEEE-Inst Electrical Electronics Engineers Inc, 2021) Tekin, Nazli; Yildiz, Huseyin Ugur; Gungor, Vehbi Cagri
In Wireless Sensor Networks (WSNs), energy-efficiency and reliability are two critical requirements for attaining a long-term stable communication performance. Using error control (EC) methods is a promising technique to improve the reliability of WSNs. EC methods are typically utilized at the network-level, where all sensor nodes use the same EC method. However, improper selection of EC methods on some nodes in the network-level strategy can reduce the energy-efficiency, thus the lifetime of WSNs. In this study, a node-level EC strategy is proposed via mixed-integer programming (MIP) formulations. The MIP model determines the optimum EC method (i.e., automatic repeat request (ARQ), forward error correction (FEC), or hybrid ARQ (HARQ)) for each sensor node to maximize the network lifetime while guaranteeing a pre-determined reliability requirement. Five meta-heuristic approaches are developed to overcome the computational complexity of the MIP model. The performances of the MIP model and meta-heuristic approaches are evaluated for a wide range of parameters such as the number of nodes, network area, packet size, minimum desired reliability criterion, transmission power, and data rate. The results show that the node-level EC strategy provides at least 4.4% prolonged lifetimes and 4.0% better energy-efficiency than the network-level EC strategies. Furthermore, one of the developed meta-heuristic approaches (i.e., extended golden section search) provides lifetimes within a 3.9% neighborhood of the optimal solutions, reducing the solution time of the MIP model by 89.6%.
Citation - WoS: 16
Citation - Scopus: 20
Assessing the Impact of COVID-19 Pandemic in Turkey With a Novel Economic Uncertainty Index
(Emerald Group Publishing Ltd, 2021) Mugaloglu, Erhan; Polat, Ali Yavuz; Tekin, Hasan; Kilic, Edanur
Purpose This study aims to measure economic uncertainty in Turkey by a novel economic uncertainty index (EUI) employing principal component analysis (PCA). We assess the impact of Covid-19 pandemic in Turkey with our constructed uncertainty index. Design/methodology/approach In order to obtain the EUI, this study employs a dimension reduction method of PCA using 14 macroeconomic indicators that spans from January 2011 to July 2020. The first principal component is picked as a proxy for the economic uncertainty in Turkey which explains 52% of total variation in entire sample. In the second part of our analysis, with our constructed EUI we conduct a structural vector autoregressions (SVAR) analysis simulating the Covid-19-induced uncertainty shock to the real economy. Findings Our EUI sensitively detects important economic/political events in Turkey as well as Covid-19-induced uncertainty rising to extremely high levels during the outbreak. Our SVAR results imply a significant decline in economic activity and in the sub-indices as well. Namely, industrial production drops immediately by 8.2% and cumulative loss over 8 months will be 15% on average. The losses in the capital and intermediate goods are estimated to be 18 and 25% respectively. Forecast error variance decomposition results imply that uncertainty shocks preserve its explanatory power in the long run, and intermediate goods production is more vulnerable to uncertainty shocks than overall industrial production and capital goods production. Practical implications The results indicate that monetary and fiscal policy should aim to decrease uncertainty during Covid-19. Moreover, since investment expenditures are affected severely during the outbreak, policymakers should impose investment subsidies. Originality/value This is the first study constructing a novel EUI which sensitively captures the critical economic/political events in Turkey. Moreover, we assess the impact of Covid-19-driven uncertainty on Turkish Economy with a SVAR model.
Citation - WoS: 18
Citation - Scopus: 20
A Simulation-Based Approximate Dynamic Programming Approach to Dynamic and Stochastic Resource-Constrained Multi-Project Scheduling Problem
(Elsevier, 2024) Satic, U.; Jacko, P.; Kirkbride, C.
We consider the dynamic and stochastic resource -constrained multi -project scheduling problem which allows for the random arrival of projects and stochastic task durations. Completing projects generates rewards, which are reduced by a tardiness cost in the case of late completion. Multiple types of resource are available, and projects consume different amounts of these resources when under processing. The problem is modelled as an infinite -horizon discrete -time Markov decision process and seeks to maximise the expected discounted long -run profit. We use an approximate dynamic programming algorithm (ADP) with a linear approximation model which can be used for online decision making. Our approximation model uses project elements that are easily accessible by a decision -maker, with the model coefficients obtained offline via a combination of Monte Carlo simulation and least squares estimation. Our numerical study shows that ADP often statistically significantly outperforms the optimal reactive baseline algorithm (ORBA). In experiments on smaller problems however, both typically perform suboptimally compared to the optimal scheduler obtained by stochastic dynamic programming. ADP has an advantage over ORBA and dynamic programming in that ADP can be applied to larger problems. We also show that ADP generally produces statistically significantly higher profits than common algorithms used in practice, such as a rule -based algorithm and a reactive genetic algorithm.
Citation - WoS: 44
Citation - Scopus: 52
CBI4.0: A Cross-Layer Approach for Big Data Gathering for Active Monitoring and Maintenance in the Manufacturing Industry 4.0
(Elsevier, 2021) Faheem, Muhammad; Butt, Rizwan Aslam; Ali, Rashid; Raza, Basit; Ngadi, Md Asri; Gungor, Vehbi Cagri
Industry 4.0 (I4.0) defines a new paradigm to produce high-quality products at the low cost by reacting quickly and effectively to changing demands in the highly volatile global markets. In Industry 4.0, the adoption of Internet of Things (IoT)-enabled Wireless Sensors (WSs) in the manufacturing processes, such as equipment, machining, assembly, material handling, inspection, etc., generates a huge volume of data known as Industrial Big Data (IBD). However, the reliable and efficient gathering and transmission of this big data from the source sensors to the floor inspection system for the real-time monitoring of unexpected changes in the production and quality control processes is the biggest challenge for Industrial Wireless Sensor Networks (IWSNs). This is because of the harsh nature of the indoor industrial environment that causes high noise, signal fading, multipath effects, heat and electromagnetic interference, which reduces the transmission quality and trigger errors in the IWSNs. Therefore, this paper proposes a novel cross-layer data gathering approach called CBI4.0 for active monitoring and control of manufacturing processes in the Industry 4.0. The key aim of the proposed CBI4.0 scheme is to exploit the multi-channel and multi-radio architecture of the sensor network to guarantee quality of service (QoS) requirements, such as higher data rates, throughput, and low packet loss, corrupted packets, and latency by dynamically switching between different frequency bands in the Multichannel Wireless Sensor Networks (MWSNs). By performing several simulation experiments through EstiNet 9.0 simulator, the performance of the proposed CBI4.0 scheme is compared against existing studies in the automobile Industry 4.0. The experimental outcomes show that the proposed scheme outperforms existing schemes and is suitable for effective control and monitoring of various events in the automobile Industry 4.0.
Operator User Management System Based on the TMF615 Standard
(Springer, 2016) Yigit, Melike; Macit, Muhammed; Gungor, V. Cagri; Kocak, Taskin; Ozhan, Oguz
Multi-vendor telecommunications networks in a typical service provider environment are managed using multiple proprietary user management systems (UMS), supplied by the operational support system (OSS) vendors. The management of a typical service provider includes communications solutions put into place between the global UMS and the local UMS. Nowadays, in service provider environments OSSs exist that use multi-vendor communications' protocols. In the telecommunications sector, the centralized management of all these different OSSs can cause serious problems for the network operation. In this respect, there is an urgent need for a standardized and centralized provisioning and auditing mechanism for the operators and their entitlements that work on these management systems. To address this need and to provide efficient operations among different service provider network components, this paper outlines the design and development of a TMF615 (Tele Management Forum) standard-based, common communication platform. In this respect, the proposed approach includes a common interface to address communication problems in multi-vendor, service provider environments. The interface and performance evaluations developed are some of the first solutions in this field, and the resulting solutions are converted into a commercial product with a high added value. In this regard, our proposed approach makes an important contribution to scientific literature and commercial applications. The realization of the proposed TMF615 standard-based interface enables the efficient and easy integration of existing and new OSSs of the service providers. In this way, a standardized interface is offered, along with a common communications platform adequate for all different systems. The vendors are thereby only responsible for application development based on specifications, and a standardized communications process is introduced for all related systems. This significantly facilitates the management of service providers, system performance is improved, and a massive cost reduction is provided at the same time. Consequently, the efficient management of network components is provided using a common standardized interface. In this respect, we aim to explain the TMF615 specifications; the evolution of UMS, OSSs and TMF615 with centralized UMS, as well as the implementation and performance evaluation of the TMF615 protocol are all explained in this paper.
Citation - WoS: 5
Citation - Scopus: 4
Polarisation Over the Meaning of Democracy: The Case of Political Parties in Turkey
(Sage Publications Ltd, 2023) Akboga, Sema; Sahin, Osman; Arik, Engin
As the primary means of political organisation, political parties remain vital to contemporary democracies, making it important to investigate their understanding of democracy. This study explores the themes with which five largest political parties in Turkey associate democracy. We studied tweets posted by official accounts of these parties' headquarters and branches, as well as by other Twitter accounts that are institutionally linked to these parties. We found significant differences between the government bloc and the opposition bloc as well as between People Alliance and Nation Alliance in terms of the themes with which they associate democracy. The government bloc and People Alliance use themes such as national will and military coups while referring to democracy. The opposition bloc and Nation Alliance emphasise themes such as equality, freedom of the press, and justice. We conclude that parties' and blocs' different attitudes towards democracy are indicators of political polarisation in Turkey.

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