Yazarlar

• Akyol, Sinem(1)
• Alatas, B.(1)
• Alatas, Bilal(1)
• Baykara, Muhammet(1)
• Bürhan, Yücel(1)
• Can, Umit(1)
• Daş, Resul(1)
• Gül, Serpil(1)
• Kaya, Buket(1)
• Kaya, Mehmet(1)

• MakaleAçık Erişim2020Scopus SJRQ2/r/munzur/3486
  Sentiment classification within online social media using whale optimization algorithm and social impact theory based optimization

  Akyol, Sinem; Alatas, Bilal

  In recent years, social networks have become an important part of daily life and are becoming increasingly important. In this study, sentiment analysis or opinion mining, which is one of the most well-known social network analysis problems, is considered as an optimization problem for the first time. In the same way, for the first time, sentiment analysis is considered as a multi-objective problem. Whale Optimization Algorithm and Social Impact Theory based Optimization Algorithm, which are the current intelligent optimization algorithms, are adapted for the sentiment analysis problem. Furthermore, memory feature is integrated into Social Impact Theory based Optimization Algorithm in order to obtain effective results in this study. The obtained results from the proposed algorithms are also compared with thirty-three supervised learning algorithms within real IMDB, Polarity, and Amazon data sets. In order to evaluate the performance of the results; accuracy percentage, precision, recall, F-Measure, and MCC that are the five most commonly used measure in the literature are used. When the results are examined, it is observed that adapted metaheuristic optimization algorithms give more successful results in sentiment analysis problem.

  AtıfScopus35·WoS27·OpenAlex43

  İncele
• Derleme MakaleAçık Erişim2019Scopus SJRQ2/r/munzur/3671
  A new direction in social network analysis: Online social network analysis problems and applications

  Can, Umit; Alatas, B.

  The use of online social networks has made significant progress in recent years as the use of the Internet has become widespread worldwide as the technological infrastructure and the use of technological products evolve. It has become more suitable to reach online social networking sites such as Facebook, Twitter, Instagram and LinkedIn via the internet and web 3.0 technologies. Thus, people have shared their views on many different topics and their emotions with other users more widely on these platforms. This means that a huge amount of data is created on platforms where millions of people connect with each other through social networks. Nevertheless, the development of computational paradigms at high speed and complexity with technological possibilities allows analysis of valuable data by means of social network analysis methods. Our goal for this paper is to present a review of novel and popular online social network analysis problems with related applications and a reference work for researchers interested in analyzing online social network data and social network problems. Unlike other individual studies we have gathered 21 online social network problems and defined them with related studies. Thus, this study is original by presenting an important source of research by explaining the problems of online social network and the studies performed in this area.

  AtıfScopus172·WoS113

  İncele
• BildiriAçık Erişim2017/r/munzur/3291
  Sosyal aǧ analizi ve veri görselleştirme araçlarinin incelenmesi ve uygulamali karşilaştirilmasi

  Bürhan, Yücel; Baykara, Muhammet; Daş, Resul

  Social network analysis has become an important issue in recent years because of the development and use of social networks widespread. Almost any kind of data can be easily obtained as valuable information about actors from these data. In this study, general information about the most used social network analysis and visualization tools are given. The author-subject network that analyzed with the help of link estimation methods, the author-writer network showing the links between co-authors is drawn and displayed visually through four different social network analysis and visualization tools.

  AtıfScopus1·OpenAlex5

  İncele
• BildiriYalnız künye2016/r/munzur/4408
  Predicting Links in Weighted Disease Networks

  Gül, Serpil; Kaya, Mehmet; Kaya, Buket

  This paper proposes a link prediction method to estimate what sort of disease risks may have been carried by the patients via surveying their and similar patients' medical histories. It is possible to make future oriented predictions with link prediction by deriving new data within a network structure. It is attempted to estimate the future structure of the network and the relations which will be created or abandoned by the individuals on the basis of the nodes within the network structure and the relations between these nodes. For this purpose, an undirected weighted disease network is first created by using the data of patients which were subjected to Hemogram test at F. rat University Hospital during 2013. In the disease network, each node represents a disease and the links represent a relationship between diseases. By the developed method, then disease risk prediction is made through a proactive approach by determining what sorts of disease risks were carried by the patients applying with certain complaints. Experimental results demonstrate the applicability of the link prediction in these networks.

  AtıfWoS11

  İncele