Turkiye Klinikleri Journal of Health Sciences

.: ORIGINAL RESEARCH
Sentiment Analysis of Natural Disaster Images Obtained from Social Media: An Experimental Study
Sosyal Medyadan Alınan Doğal Afet Görüntülerinin Duygu Analizi: Deneysel Araştırma
Gülcan DEMİRa , Gözde ÖZSEZERb , Cüneyt ÇALIŞKANc , Hüseyin KOÇAKd
aSinop University Vocational School of Health Service, Department of Medical Services and Techniques, Sinop, Türkiye
bÇanakkale Onsekiz Mart University Faculty of Health Sciences, Department of Nursing, Çanakkale, Türkiye
cUniversity of Health Sciences Hamidiye Faculty of Health Sciences, Department of Emergency Aid and Disaster Management, İstanbul, Türkiye
dÇanakkale Onsekiz Mart University Faculty of Health Sciences, Department of Emergency Aid and Disaster Management, Çanakkale, Türkiye
Turkiye Klinikleri J Health Sci. 2024;9(4):642-51
doi: 10.5336/healthsci.2024-103042
Article Language: EN
Full Text
ABSTRACT
 Objective: The frequency of natural disasters worldwide is increasing, and social networks have become popular sources of crucial data for analyzing images' emotions. Although the analysis of disaster-related images is a relatively new field, this study aims to identify the emotional responses evoked by images shared on social media. Material and Methods: In this four-stage study, a total of 5,203 free and openly accessible images were scraped from various social media platforms, and emotion categories associated with these images were selected. The images were converted to RGB format and resized after undergoing preprocessing. Normalization of the visual pixels was performed. Various deep learning (DL) models were examined for visual sentiment analysis, and their performance was compared using metrics. Subsequently, emotion classification was performed using Inception-v3, which yielded the most reliable results. Results: The most suitable DL model among different pre-trained DL models was determined to be Inception-v3 with a performance metric of 81.2%. The analysis of the emotions depicted in the images revealed that 71.9% (n=3,741) were classified as negative, while 8.0% (n=781) were classified as neutral. Conclusion: These results indicate that visual sentiment analysis of social media data can significantly enhance disaster response efforts. By identifying early warning messages, updating disaster-related information, and monitoring user-generated content, this approach supports more effective data analytics and information dissemination. Consequently, the use of advanced DL models like Inception-v3 in analyzing emotional content from social media can provide valuable insights and improve the efficiency and effectiveness of disaster management strategies.

Keywords: Social media; artificial intelligence; deep learning; sentiment analysis; natural disaster
ÖZET
 Amaç: Dünya genelinde doğal afetlerin sıklığı artmaktadır ve sosyal ağlar, görüntülerin duygusal analizi için kritik veri kaynakları hâline gelmiştir. Doğal afetlerle ilgili görüntülerin analizi nispeten yeni bir alandır, bu çalışma ise sosyal medyada paylaşılan görüntülerin uyandırdığı duygusal tepkileri tanımlamayı amaçlamaktadır. Gereç ve Yöntemler: Bu 4 aşamalı çalışmada, çeşitli sosyal medya platformlarından toplam 5.203 ücretsiz ve açıkça erişilebilir görüntü çekildi ve bu görüntülerle ilişkilendirilen duygu kategorileri seçildi. Görseller, ön işleme tabi tutularak RGB formatına dönüştürüldü ve yeniden boyutlandırıldı. Görsel piksellerinin normalizasyonu yapıldı. Görsel duygu analizi için çeşitli derin öğrenme [deep learning (DL)] modelleri incelendi ve performansları metrikler kullanılarak karşılaştırıldı. Daha sonra, en güvenilir sonuçları veren Inception-v3 kullanılarak duygu sınıflandırması yapıldı. Bulgular: Önceden eğitilmiş farklı DL modellerinin performans metrikleri içerisinde en uygun derin öğrenme modeli %81,2 ile Inception-v3 olduğu belirlendi. Görüntülerde tasvir edilen duyguların analizi, 3.741'i (%71,9) negatif olarak sınıflandırılırken, 781'i (%8,0) nötr olarak sınıflandırıldığını ortaya koydu. Sonuç: Bu sonuçlar, sosyal medya verilerinin görsel duygu analizinin, afet müdahale çabalarını önemli ölçüde artırabileceğini göstermektedir. Erken uyarı mesajlarını belirleyerek, afetle ilgili bilgileri güncelleyerek ve kullanıcı tarafından oluşturulan içeriği izleyerek, bu yaklaşım daha etkili veri analitiği ve bilgi yayılımını desteklemektedir. Sonuç olarak, sosyal medyadan duygusal içerik analizinde Inception-v3 gibi ileri derin öğrenme modellerinin kullanılması, değerli içgörüler sağlayabilir ve afet yönetim stratejilerinin verimliliğini ve etkinliğini artırabilir.

Anahtar Kelimeler: Sosyal medya; yapay zekâ; derin öğrenme; duygu analizi; doğal afet
REFERENCES:
  1. Hoque MA-A, Phinn SR, Roelfsema C, Childs I. Tropical cyclone disaster management using remote sensing and spatial analysis: a review. International Journal of Disaster Risk Reduction. 2017;22:345-54. [Crossref] 
  2. Kc U, Garg S, Hilton JE, Aryal J, Forbes-Smith N. Cloud computing in natural hazard modeling systems: current research trends and future directions. International Journal of Disaster Risk Reduction. 2019;38:101188. [Crossref] 
  3. Xiong J, Hswen Y, Naslund JA. Digital surveillance for monitoring environmental health threats: a case study capturing public opinion from Twitter about the 2019 Chennai water crisis. Int J Environ Res Public Health. 2020;17(14):5077. [Crossref]  [PubMed]  [PMC] 
  4. Tim Y, Pan SL, Ractham P, Kaewkitipong L. Digitally enabled disaster response: the emergence of social media as boundary objects in a flooding disaster. Information Systems Journal. 2016;27(2):197-232. [Crossref] 
  5. Ennaji FZ, Fazziki AE, Abdallaoui HEAE, Benslimane D, Sadgal M. A product reputation framework based on social multimedia content. International Journal of Web Information Systems. 2019;16(1):95-113. [Crossref] 
  6. EM-DAT [Internet]. [Cited: June 20, 2023]. The International Disaster Database Belgium: Centre for Research on the Epidemiology of Disasters-CRED; 2023. Available from: [Link] 
  7. Hassan SZ, Ahmad K, Hicks S, Halvorsen P, Al-Fuqaha A, Conci N, et al. Visual sentiment analysis from disaster images in social media. Sensors. 2022;22(10):3628. [Crossref] 
  8. Graham NA, Jennings S, MacNeil MA, Mouillot D, Wilson SK. Predicting climate-driven regime shifts versus rebound potential in coral reefs. Nature. 2015;518(7537):94-7. [Crossref]  [PubMed] 
  9. Sufi F, Khalil I. Automated disaster monitoring from social media posts using ai-based location intelligence and sentiment analysis. IEEE Transactions on Computational Social Systems. 2022;PP(99):1-11. [Crossref] 
  10. Yum S. Sentiment analyses of Twitter for winter storm leo. In: Information Resources Management Association, editor. Research Anthology on Managing Crisis and Risk Communications. Hershey, PA, USA: IGI Global; 2023. p.790-809. [Crossref] 
  11. Mittal N, Sharma D, Joshi M. Image sentiment analysis using deep learning. IEEE/WIC/ACM International Conference on Web Intelligence. 2018. p.684-7 [Crossref] 
  12. Ortis A, Farinella G, Battiato S. An overview on image sentiment analysis: methods, datasets and current challenges. SciTePress. 2019. p.290-300. [Link] 
  13. Baratloo A, Hosseini M, Negida A, El Ashal G. Part 1: Simple Definition and Calculation of Accuracy, Sensitivity and Specificity. Emerg (Tehran). 2015;3(2):48-9. [PubMed]  [PMC] 
  14. Krizhevsky A, Sutskever I, Hinton GE. ImageNet classification with deep convolutional neural networks. Commun ACM. 2017;60(6):84-90. [Crossref] 
  15. Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image recognition. arXiv. 2014. [Link] 
  16. Andersen RE, Nalpantidis L, Ravn O, Boukas E. Investigating Deep Learning Architectures towards Autonomous Inspection for Marine Classification. 2020 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR). 2020:197-204. [Crossref] 
  17. He K, Zhang X, Ren S, Sun J. Deep Residual Learning for Image Recognition. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2016 27-30 June 2016. [Crossref] 
  18. Dai J, He K, Sun J. Instance-aware Semantic Segmentation via Multi-task Network Cascades. arXiv. 2015. [Crossref] 
  19. Chen LC, Papandreou G, Kokkinos I, Murphy K, Yuille AL. DeepLab: semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2018;40(4):834-48. [Crossref] 
  20. Deng J, Dong W, Socher R, Li LJ, Kai L, Li F-F, editors. ImageNet: A large-scale hierarchical image database. 2009 IEEE Conference on Computer Vision and Pattern Recognition 2009 20-25 June 2009. [Crossref] 
  21. Zhou B, Lapedriza À, Xiao J, Torralba A, Oliva A. Learning Deep Features for Scene Recognition using Places Database. Advances in Neural Information Processing Systems. 2015;1. [Link] 
  22. Meena G, Mohbey K, Kumar S, Chawda R, Gaikwad S. Image-Based Sentiment Analysis Using InceptionV3 Transfer Learning Approach. SN Computer Science. 2023;4. [Crossref] 
  23. Yu H, Sun H, Li J, Shi L, Bao N, Li H, et al. Effective diagnostic model construction based on discriminative breast ultrasound image regions using deep feature extraction. Med Phys. 2021;48(6):2920-8. [Crossref]  [PubMed] 
  24. Salman Al-Tameemi IK, Feizi-Derakhshi MR, Pashazadeh S, Asadpour M. Multi-model fusion framework using deep learning for visual-textual sentiment classification. Computers Materials and Continua. 2023;76(2):2145-77. [Crossref] 
  25. Al Husaini MAS, Habaebi MH, Gunawan TS, Islam MR, Elsheikh EAA, Suliman FM. Thermal-based early breast cancer detection using inception V3, inception V4 and modified inception MV4. Neural Comput Appl. 2022;34(1):333-48. [Crossref]  [PubMed]  [PMC] 
  26. Wu W, Li J, Ye J, Wang Q, Zhang W, Xu S. Differentiation of glioma mimicking encephalitis and encephalitis using multiparametric MR-based deep learning. Front Oncol. 2021;11:639062. [Crossref]  [PubMed]  [PMC] 
  27. Mkhatshwa J, Kavu T, Daramola O. Analysing the performance and interpretability of CNN-based architectures for plant nutrient deficiency identification. Computation. 2024;12(6):113. [Crossref] 
  28. Saleh N, Wahed MA, Salaheldin AM. Transfer learning-based platform for detecting multi-classification retinal disorders using optical coherence tomography images. International Journal of Imaging Systems and Technology. 2021;32(3):740-52. [Crossref] 
  29. Fang X, Li W, Huang J, Li W, Feng Q, Han Y, et al. Ultrasound image intelligent diagnosis in community-acquired pneumonia of children using convolutional neural network-based transfer learning. Front Pediatr. 2022;10:1063587. [Crossref]  [PubMed]  [PMC] 
  30. Xiao T, Liu L, Li K, Qin W, Yu S, Li Z. Comparison of transferred deep neural networks in ultrasonic breast masses discrimination. Biomed Res Int. 2018;2018:4605191. [Crossref]  [PubMed]  [PMC] 
  31. Morellos A, Pantazi XE, Paraskevas C, Moshou D. Comparison of deep neural networks in detecting field grapevine diseases using transfer learning. Remote Sensing. 2022;14(18):4648. [Crossref] 
  32. Szegedy C, Liu W, Jia Y, Sermanet P, Reed S, Anguelov D, et al. Going deeper with convolutions. arXiv. 2015. [Crossref] 
  33. Mvoulana A, Kachouri R, Akil M. Fine-tuning convolutional neural networks: a comprehensive guide and benchmark analysis for glaucoma screening. Italy: 25th International Conference in Pattern Recognition; 2021. [Crossref] 
  34. Khudaier AH, Radhi AM. Binary classification of diabetic retinopathy using CNN architecture. Iraqi Journal of Science. 2024;65(2):963-78. [Crossref] 
  35. Sukegawa S, Tanaka F, Nakano K, Hara T, Yoshii K, Yamashita K, et al. Effective deep learning for oral exfoliative cytology classification. Sci Rep. 2022;12(1):13281. [Crossref]  [PubMed]  [PMC] 

.: Up To Date

.: Process List

Login

 Forgot your password?

 New Registration  

Contact

Ortadoğu Reklam Tanıtım Yayıncılık Turizm Eğitim İnşaat Sanayi ve Ticaret A.Ş.

.: Address

Turkocagi Caddesi No:30 06520 Balgat / ANKARA
Phone: +90 312 286 56 56
Fax: +90 312 220 04 70
E-mail: info@turkiyeklinikleri.com

.: Manuscript Editing Department

Phone: +90 312 286 56 56/ 2
E-mail: yaziisleri@turkiyeklinikleri.com

.: English Language Redaction

Phone: +90 312 286 56 56/ 145
E-mail: tkyayindestek@turkiyeklinikleri.com

.: Marketing Sales-Project Department

Phone: +90 312 286 56 56/ 142
E-mail: reklam@turkiyeklinikleri.com

.: Subscription and Public Relations Department

Phone: +90 312 286 56 56/ 118
E-mail: abone@turkiyeklinikleri.com

.: Customer Services

Phone: +90 312 286 56 56/ 118
E-mail: satisdestek@turkiyeklinikleri.com

1. TERMS OF USE

1.1. To use the web pages with http://www.turkiyeklinikleri.com domain name or the websites reached through the sub domain names attached to the domain name (They will be collectively referred as "SITE"), please read the conditions below. If you do not accept these terms, please cease to use the "SITE." "SITE" owner reserves the right to change the information on the website, forms, contents, the "SITE," "SITE" terms of use anytime they want.

1.2. The owner of the "SITE" is Ortadoğu Advertisement Presentation Publishing Tourism Education Architecture Industry and Trade Inc. (From now on it is going to be referred as "Turkiye Klinikleri", shortly) and it resides at Turkocagi cad. No:30, 06520 Balgat Ankara. The services in the "SITE" are provided by "Turkiye Klinikleri."

1.3. Anyone accessing the "SITE" with or without a fee whether they are a natural person or a legal identity is considered to agree these terms of use. In this contract hereby, "Turkiye Klinikleri" may change the stated terms anytime. These changes will be published in the "SITE" periodically and they will be valid when they are published. Any natural person or legal identity benefiting from and reaching to the "SITE" are considered to be agreed to any change on hereby contract terms done by "Turkiye Klinikleri."

1.4. The "Terms of Use" hereby is published in the website with the last change on March 30th 2014 and the "SITE" is activated by enabling the access to everyone. The "Terms of Use" hereby is also a part of the any "USER Contract" was and/or will be done with the users using "Turkiye Klinikleri" services with or without a fee an inseparable.

2. DEFINITIONS

2.1. "SITE": A website offering different kind of services and context with a certain frame determined by "Turkiye Klinikleri" and it is accessible on-line on http://www.turkiyeklinikleri.com domain name and/or subdomains connected to the domain name.

2.2. USER: A natural person or a legal identity accessing to the "SITE" through online settings.

2.3. LINK: A link enabling to access to another website through the "SITE", the files, the context or through another website to the "SITE", the files and the context.

2.4. CONTEXT: Any visual, literary and auditory images published in the "Turkiye Klinikleri", "SITE" and/or any website or any accessible information, file, picture, number/figures, price, etc.

2.5. "USER CONTRACT": An electronically signed contract between a natural or a legal identity benefiting from special services "Turkiye Klinikleri" will provide and "Turkiye Klinikleri".

3. SCOPE OF THE SERVICES

3.1. "Turkiye Klinikleri" is completely free to determine the scope and quality of the services via the "SITE".

3.2. To benefit the services of "Turkiye Klinikleri" "SITE", the "USER" must deliver the features that will be specified by "Turkiye Klinikleri". "Turkiye Klinikleri" may change this necessity any time single-sided.

3.3. Not for a limited number, the services "Turkiye Klinikleri" will provide through the "SITE" for a certain price or for free are;

- Providing scientific articles, books and informative publications for health industry.

- Providing structural, statistical and editorial support to article preparation stage for scientific journals.

4. GENERAL PROVISIONS

4.1. "Turkiye Klinikleri" is completely free to determine which of the services and contents provided in the "SITE" will be charged.

4.2. People benefiting from the services provided by "Turkiye Klinikleri" and using the website can use the "SITE" only according to the law and only for personal reasons. Users have the criminal and civil liability for every process and action they take in the "SITE". Every USER agrees, declares and undertakes that they will not proceed by any function or action infringement of rights of "Turkiye Klinikleri"s and/or other third parties', they are the exclusive right holder on usage, processing, storage, made public and revealing any written, visual or auditory information reported to Turkiye Klinikleri" and/or "SITE" to the third parties. "USER" agrees and undertakes that s/he will not duplicate, copy, distribute, process, the pictures, text, visual and auditory images, video clips, files, databases, catalogs and lists within the "SITE", s/he will not be using these actions or with other ways to compete with "Turkiye Klinikleri", directly or indirectly.

4.3. The services provided and the context published within the "SITE" by third parties is not under the responsibility of "Turkiye Klinikleri", institutions collaborated with "Turkiye Klinikleri", "Turkiye Klinikleri" employee and directors, "Turkiye Klinikleri" authorized salespeople. Commitment to accuracy and legality of the published information, context, visual and auditory images provided by any third party are under the full responsibility of the third party. "Turkiye Klinikleri" does not promise and guarantee the safety, accuracy and legality of the services and context provided by a third party.

4.4. "USER"s cannot act against "Turkiye Klinikleri", other "USER"s and third parties by using the "SITE". "Turkiye Klinikleri" has no direct and/or indirect responsibility for any damage a third party suffered or will suffer regarding "USER"s actions on the "SITE" against the rules of the hereby "Terms of Use" and the law.

4.5. "USER"s accept and undertake that the information and context they provided to the "SITE" are accurate and legal. "Turkiye Klinikleri" is not liable and responsible for promising and guaranteeing the verification of the information and context transmitted to "Turkiye Klinikleri" by the "USER"s, or uploaded, changed and provided through the "SITE" by them and whether these information are safe, accurate and legal.

4.6. "USER"s agree and undertake that they will not perform any action leading to unfair competition, weakening the personal and commercial credit of "Turkiye Klinikleri" and a third party,  encroaching and attacking on personal rights within the "SITE" in accordance with the Turkish Commercial Code Law.

4.7. "Turkiye Klinikleri" reserves the right to change the services and the context within the "SITE"  anytime. "Turkiye Klinikleri" may use this right without any notification and timelessly. "USER"s have to make the changes and/or corrections "Turkiye Klinikleri" required immediately. Any changes and/or corrections that are required by "Turkiye Klinikleri", may be made by "Turkiye Klinikleri" when needed. Any harm, criminal and civil liability resulted or will result from changes and/or corrections required by "Turkiye Klinikleri" and were not made on time by the "USER"s belongs completely to the users.

4.8. "Turkiye Klinikleri" may give links through the "SITE" to other websites and/or "CONTEXT"s and/or folders that are outside of their control and owned and run by third parties. These links are provided for ease of reference only and do not hold qualification for support the respective web SITE or the admin or declaration or guarantee for the information inside. "Turkiye Klinikleri" does not hold any responsibility over the web-sites connected through the links on the "SITE", folders and context, the services or products on the websites provided through these links or their context.

4.9. "Turkiye Klinikleri" may use the information provided to them by the "USERS" through the "SITE" in line with the terms of the "PRIVACY POLICY" and "USER CONTRACT". It may process the information or classify and save them on a database. "Turkiye Klinikleri" may also use the USER's or visitor's identity, address, e-mail address, phone number, IP number, which sections of the "SITE" they visited, domain type, browser type, date and time information to provide statistical evaluation and customized services.

5. PROPRIETARY RIGHTS

5.1. The information accessed through this "SITE" or provided by the users legally and all the elements (including but not limited to design, text, image, html code and other codes) of the "SITE" (all of them will be called as studies tied to "Turkiye Klinikleri"s copyrights) belongs to "Turkiye Klinikleri". Users do not have the right to resell, process, share, distribute, display or give someone permission to access or to use the "Turkiye Klinikleri" services, "Turkiye Klinikleri" information and the products under copyright protection by "Turkiye Klinikleri". Within hereby "Terms of Use" unless explicitly permitted by "Turkiye Klinikleri" nobody can reproduce, process, distribute or produce or prepare any study from those under "Turkiye Klinikleri" copyright protection.

5.2. Within hereby "Terms of Use", "Turkiye Klinikleri" reserves the rights for "Turkiye Klinikleri" services, "Turkiye Klinikleri" information, the products associated with "Turkiye Klinikleri" copyrights, "Turkiye Klinikleri" trademarks, "Turkiye Klinikleri" trade looks or its all rights for other entity and information it has through this website unless it is explicitly authorized by "Turkiye Klinikleri".

6. CHANGES IN THE TERMS OF USE

"Turkiye Klinikleri" in its sole discretion may change the hereby "Terms of Use" anytime announcing within the "SITE". The changed terms of the hereby "Terms of Use" will become valid when they are announced. Hereby "Terms of Use" cannot be changed by unilateral declarations of users.

7. FORCE MAJEURE

"Turkiye Klinikleri" is not responsible for executing late or never of this hereby "Terms of Use", privacy policy and "USER Contract" in any situation legally taken into account as force majeure. Being late or failure of performance or non-defaulting of this and similar cases like this will not be the case from the viewpoint of "Turkiye Klinikleri", and "Turkiye Klinikleri" will not have any damage liability for these situations. "Force majeure" term will be regarded as outside of the concerned party's reasonable control and any situation that "Turkiye Klinikleri" cannot prevent even though it shows due diligence. Also, force majeure situations include but not limited to natural disasters, rebellion, war, strike, communication problems, infrastructure and internet failure, power cut and bad weather conditions.

8. LAW AND AUTHORISATION TO FOLLOW

Turkish Law will be applied in practicing, interpreting the hereby "Terms of Use" and managing the emerging legal relationships within this "Terms of Use" in case of finding element of foreignness, except for the rules of Turkish conflict of laws. Ankara Courts and Enforcement Offices are entitled in any controversy happened or may happen due to hereby contract.

9. CLOSING AND AGREEMENT

Hereby "Terms of Use" come into force when announced in the "SITE" by "Turkiye Klinikleri". The users are regarded to agree to hereby contract terms by using the "SITE". "Turkiye Klinikleri" may change the contract terms and the changes will be come into force by specifying the version number and the date of change on time it is published in the "SITE".

 

30.03.2014

Privacy Policy

We recommend you to read the terms of use below before you visit our website. In case you agree these terms, following our rules will be to your favor. Please read our Terms of Use thoroughly.

www.turkiyeklinikleri.com website belongs to Ortadoğu Advertisement Presentation Publishing Tourism Education Architecture Industry and Trade Inc. and is designed in order to inform physicians in the field of health

www.turkiyeklinikleri.com cannot reach to user’s identity, address, service providers or other information. The users may send this information to the website through forms if they would like to. However, www.turkiyeklinikleri.com may collect your hardware and software information. The information consists of your IP address, browser type, operating system, domain name, access time, and related websites. www.turkiyeklinikleri.com cannot sell the provided user information (your name, e-mail address, home and work address, phone number) to the third parties, publish it publicly, or keep it in the website. Gathered information has a directing feature to be a source for the website’s visitor profile, reporting and promotion of the services.

www.turkiyeklinikleri.com uses the taken information:

-To enhance, improve and maintain the quality of the website

-To generate visitor’s profile and statistical data

-To determine the tendency of the visitors on using our website

-To send print publications/correspondences

-To send press releases or notifications through e-mail

-To generate a list for an event or competition

By using www.turkiyeklinikleri.com you are considered to agree that;

-Ortadoğu Advertisement Presentation Publishing Tourism Education Architecture Industry and Trade Inc. cannot be hold responsible for any user’s illegal and immoral behavior,

-Terms of use may change from time to time,

-It is not responsible for other websites’ contents it cannot control or the harms they may cause although it uses the connection they provided.

Ortadoğu Advertisement Presentation Publishing Tourism Education Architecture Industry and Trade Inc. may block the website to users in the following events:

-Information with wrong, incomplete, deceiving or immoral expressions is recorded to the website,

-Proclamation, advertisement, announcement, libelous expressions are used against natural person or legal identity,

-During various attacks to the website,

-Disruption of the website because of a virus.

Written, visual and audible materials of the website, including the code and the software are under protection by legal legislation.

Without the written consent of Ortadoğu Advertisement Presentation Publishing Tourism Education Architecture Industry and Trade Inc. the information on the website cannot be downloaded, changed, reproduced, copied, republished, posted or distributed.

All rights of the software and the design of the website belong to Ortadoğu Advertisement Presentation Publishing Tourism Education Architecture Industry and Trade Inc.

Ortadoğu Advertisement Presentation Publishing Tourism Education Architecture Industry and Trade Inc. will be pleased to hear your comments about our terms of use. Please share the subjects you think may enrich our website or if there is any problem regarding our website.

info@turkiyeklinikleri.com