Yıl 2018, Cilt 4, Sayı 3, Sayfalar 183 - 196 2018-12-24

Finding Influencers on Twitter with Using Machine Learning Classification Algorithms
Twitter Üzerindeki Etkili Bireylerin Makine Öğrenmesi Sınıflandırma Algoritmaları İle Tespiti

Mehmet Şimşek [1] , Abdullah Talha Kabakuş [2]

11 44

Microblog sites are environments where people follow people. With this feature, a microblog site is a convenient environment for spreading an opinion or introducing a new product. The key point is determination of individuals who maximize the spreading. This problem is known as Influence Maximization (IM) and has attracted attention of many researchers. Many studies in the literature have modeled IM problem on graphs for different propagation models such as Independent Cascade (IC) and Linear Threshold (LT). However, microblogs like Twitter have their own features. Many works on IM in Twitter derive new metrics from user and tweet features; apply a greedy approach for selecting influencers. In this study, we adopted different approach for IM problem, and we dealt it as a classification problem. Firstly, we collected data on International Women Day 2018; empirically we labeled the users as either influencer candidates or non-influencers; then we applied classification methods for classifying users into one class with using features of users. By this way, we obtained an influencer candidates set, which is very smaller than entire dataset. Experimental results show that making selection with using same heuristic (namely MF) from the reduced influencer candidates set outperforms making selection from entire dataset.

Mikroblog siteleri insanların birbirlerini takip ettikleri ortamlardır. Bu özellikleri ile bir microblog sitesi bir fikrin ya da yeni bir ürünün yayılması için elverişli bir ortamdır. Buradaki anahtar nokta, yayılımı maksimize edecek bireylerin tespitidir. Bu problem, Etki Maksimizasyonu (EM) olarak bilinir ve birçok araştırmacının ilgisini çekmiştir. Literatürdeki birçok çalışma EM problemini graflar üzerinde Independent Cascade (IC) ve Linear Threshold (LT) yayılım modelleri için ele almıştır. Ne var ki, Twitter gibi microblog sitelerinin kendi özellikleri ve vardır. Twitter üzerinde EM problemini ele almış olan birçok çalışma, kullanıcı ve tweet özelliklerinden yeni ölçütler geliştirme ve bu ölçütleri kullanan bir aç gözlü algoritma ile etkin bireyleri seçme yolunu izler. Bu çalışmada biz EM problemi farklı bir yaklaşım uyguladık ve problemi bir sınıflandırma problemi olarak ele aldık. İlk olarak, 2018 Uluslararası Kadınlar Gününde veri topladık; kullanıcıları deneysel olarak etkili bireyler ve etkili olmayan bireyler olarak etiketledik; son olarak bireyleri etkili ya da etkili olmayan diye sınıflara ayırmak için sınıflandırma algoritmalarını kullandık. Bu şekilde, ana verisetinden oldukça küçük olan bir etkili bireyler kümesi elde ettik. Deneysel sonuçlar, aynı parametreyi kullanarak indirgenmiş kümeden seçim yapılmasının, bütün veriseti üzerinden seçim yapılmasına göre çok daha başarılı sonuçlar verdiğini göstermiştir.

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Birincil Dil en
Konular Bilgisayar Bilimleri, Bilgi Sistemleri
Dergi Bölümü Araştırma Makalesi
Yazarlar

Orcid: 0000-0002-9797-5028
Yazar: Mehmet Şimşek
Kurum: DÜZCE ÜNİVERSİTESİ
Ülke: Turkey


Orcid: 0000-0003-2181-4292
Yazar: Abdullah Talha Kabakuş
Kurum: DÜZCE ÜNİVERSİTESİ
Ülke: Turkey


Bibtex @araştırma makalesi { gmbd468269, journal = {Gazi Mühendislik Bilimleri Dergisi (GMBD)}, issn = {2149-4916}, eissn = {2149-9373}, address = {Aydın KARAPINAR}, year = {2018}, volume = {4}, pages = {183 - 196}, doi = {}, title = {Finding Influencers on Twitter with Using Machine Learning Classification Algorithms}, key = {cite}, author = {Şimşek, Mehmet and Kabakuş, Abdullah Talha} }
APA Şimşek, M , Kabakuş, A . (2018). Finding Influencers on Twitter with Using Machine Learning Classification Algorithms. Gazi Mühendislik Bilimleri Dergisi (GMBD), 4 (3), 183-196. Retrieved from http://dergipark.gov.tr/gmbd/issue/41439/468269
MLA Şimşek, M , Kabakuş, A . "Finding Influencers on Twitter with Using Machine Learning Classification Algorithms". Gazi Mühendislik Bilimleri Dergisi (GMBD) 4 (2018): 183-196 <http://dergipark.gov.tr/gmbd/issue/41439/468269>
Chicago Şimşek, M , Kabakuş, A . "Finding Influencers on Twitter with Using Machine Learning Classification Algorithms". Gazi Mühendislik Bilimleri Dergisi (GMBD) 4 (2018): 183-196
RIS TY - JOUR T1 - Finding Influencers on Twitter with Using Machine Learning Classification Algorithms AU - Mehmet Şimşek , Abdullah Talha Kabakuş Y1 - 2018 PY - 2018 N1 - DO - T2 - Gazi Mühendislik Bilimleri Dergisi (GMBD) JF - Journal JO - JOR SP - 183 EP - 196 VL - 4 IS - 3 SN - 2149-4916-2149-9373 M3 - UR - Y2 - 2018 ER -
EndNote %0 Gazi Mühendislik Bilimleri Dergisi (GMBD) Finding Influencers on Twitter with Using Machine Learning Classification Algorithms %A Mehmet Şimşek , Abdullah Talha Kabakuş %T Finding Influencers on Twitter with Using Machine Learning Classification Algorithms %D 2018 %J Gazi Mühendislik Bilimleri Dergisi (GMBD) %P 2149-4916-2149-9373 %V 4 %N 3 %R %U
ISNAD Şimşek, Mehmet , Kabakuş, Abdullah Talha . "Twitter Üzerindeki Etkili Bireylerin Makine Öğrenmesi Sınıflandırma Algoritmaları İle Tespiti". Gazi Mühendislik Bilimleri Dergisi (GMBD) 4 / 3 (Aralık 2018): 183-196.