Users' Traces for Enhancing Arabic Facebook Search

International audienceThis paper proposes an approach on Facebook search in Arabic, which exploits several users' traces (e.g. comment, share, reactions) left on Facebook posts to estimate their social importance. Our goal is to show how these social traces (signals) can play a vital role in improving Arabic Facebook search. Firstly, we identify polarities (positive or negative) carried by the textual signals (e.g. comments) and non-textual ones (e.g. the reactions love and sad) for a given Facebook post. Therefore, the polarity of each comment expressed on a given Facebook post, is estimated on the basis of a neural sentiment model in Arabic language. Secondly, we group signals according to their complementarity using features selection algorithms. Thirdly, we apply learning to rank (LTR) algorithms to re-rank Facebook search results based on the selected groups of signals. Finally, experiments are carried out on 13,500 Facebook posts, collected from 45 topics in Arabic language. Experiments results reveal that Random Forests combined with ReliefFAttributeEval (RLF) was the most effective LTR approach for this task

A FRAMEWORK FOR ARABIC SENTIMENT ANALYSIS USING MACHINE LEARNING CLASSIFIERS

International audienceIn recent years, the use of Internet and online comments, expressed in natural language text, have increased significantly. However, it is difficult for humans to read all these comments and classify them appropriately. Consequently, an automatic approach is required to classify the unstructured data. In this paper, we propose a framework for Arabic language comprising of three steps: pre-processing, feature extraction and machine learning classification. The main aim of the proposed framework is to exploit the combination of different Arabic linguistic features. We evaluate the framework using two benchmark Arabic tweets datasets (ASTD, ATA), which enable sentiment polarity detection in general Arabic and Jordanian dialects. Comparative simulation results show that machine learning classifiers such as Support Vector Machine (SVM), Naive Bayes, MultiLayer Perceptron (MLP) and Logistic Regression-based produce the best performance by using a combination of n-gram features from Arabic tweets datasets. Finally, we evaluate the performance of our proposed framework using an Ensemble classifier approach, with promising results

Emotions in Citizens’ Comments on the Internet as Predictors of Election Success

Citizens express attitudes toward politicians and policies as special kinds of judgments colored by emotions and we call them sentiments. In this way, they participate in the process of creating public opinion, which can be manifested in different ways. Nowadays, it could be expressed through citizen comments on Websites, such as news portals, blogs and forums. Sentiment analysis of comments can give us an insight into the fundamental beliefs of citizens and their political profiles, which is very important for politicians when they want to explore public opinion, especially at the time of elections. This method is based on the extraction of sentiments expressed by words and terms in citizen comments on the Web. This paper presents the results of automated or manual sentiment analysis of citizens’ comments about politics on news websites in different countries. It shows that citizens generally have a dominantly negative public opinion on politicians and politics and that different news websites gather specific political profiles of citizens. The comparison between the characteristics of public opinion and election results suggests that the results of sentiment analysis can serve as predictors of election success

Relationship between participative journalism and results of Split mayoral election in 2013

U radu su primjenom metoda studije više slučaja i sadržajne analize istraživane odlike participativnog novinarstva i konverzacija građana novinara u razdoblju prije i za vrijeme predizborne kampanje za izbor splitskog gradonačelnika 2013. na pet hrvatskih novinskih portala: 24 sata, Indeks, T-portal, Slobodna Dalmacija i Dalmacija News, te je pomoću utvrđivanja semantičke orijentacije (SO) komentara provedena ručna analiza sentimenata izraženih prema kandidatima i njihovim odlikama: sposobnost, pristojnost, odgovornost, moralnost, izgled, domoljublje i kriminalnost. Tijekom analize izrađen je rječnik s 4913 izraza i riječi koje izražavaju sentimente prema političarima i njihovim odlikama. Na temelju strukture 604 konverzacije i analize 15 715 komentara utvrđeni su niska argumentiranost i niska interaktivnost konverzacije, zbog čega je zaključeno da je konverzacija građana novinara na istraživanim portalima imala nisku razinu javne rasprave. Građani su novinari na svim istraživanim portalima jedni prema drugima i prema kandidatima izražavali pretežito negativne sentimente, osim u slučaju Marijane Puljak. Usporedba raspodjele rezultata za SO komentara pokazala je da građani novinari na istraživanim portalima ne pripadaju istoj populaciji. Novinski su se portali međusobno razlikovali i prema: broju objavljenih članaka o kandidatima, broju komentara o kandidatima i broju građana novinara koji su sudjelovali u konverzaciji. Na svim je portalima izražena dominacija novinskih članaka i broja komentara građana novinara o Željku Kerumu, te je na gotovo svim portalima uočeno da je u kategoriji Domoljublje najlošije bio ocijenjen SDP-ov kandidat Ivo Baldasar, a u kategoriji Kriminalnost HDZ-ov kandidat Vjekoslav Ivanišević. Na dva novinska portala koji su objavili novinske članke o svim kandidatima (Slobodna Dalmacija i Dalmacija News) utvrđena je povezanost izbornih rezultata s brojem objavljenih članaka o kandidatu, brojem komentara o kandidatu, brojem građana novinara koji su komentirali kandidata i brojem građana novinara koji su prema kandidatu bili pozitivno ili negativno orijentirani. Rezultati ovog istraživanja u slučajevima pet hrvatskih novinskih portala pokazali su da postoji povezanost između participativnog novinarstva i izbornih rezultata te da je konverzacija građana novinara bila daleko od ideala javne rasprave kakvu opisuje Habermas (1996).Using the methods cross-case analysis and content analysis this dissertation investigated the characteristics of participatory journalism and conversation between citizen journalists in the period before and during the election campaign for the election of the mayor of Split in 2013. in five croatian news portal: 24 sata, Index, T-portal, Slobodna Dalmacija and Dalmacija News, and by determining the semantic orientation (SO) of comments performed manual sentiment analysis, exploring sentiments expressed toward candidates and their qualities: competence, politeness, responsibility, morality, appearance, patriotism and criminality. During the analysis dictionary was built with 4 913 words and phrases that express the sentiments toward politicians and their characteristics. Based on the structure of 604 conversations and analysis of 15 715 comments low argumentation and low interactivity of conversation were found, a it is concluded that the conversation between citizen journalists in the studied portals had a low level of public deliberation. Citizens journalists at all investigated portals expressed predominantly negative sentiments toward each other and toward the candidates, except in the case of Marijana Puljak. Comparison of the distribution of results for SO of comments showed that citizen journalists in the studied portals do not belong to the same population. News portals are also different from each other in relation to: the number of articles about the candidates, the number of comments on the candidates and the number of citizen journalists who participated in the conversation. Domination of newspaper articles and the number of comments on Željko Kerum is common for all the portals, and on almost all portals are observed that in the category Patriotism SDP candidate Ivo Baldasar got lowest score, and in the category Criminality HDZ candidate Vjekoslav Ivaniševic got lowest score. On two news portals that have published newspaper articles about all the candidates (Slobodna Dalmacija and Dalmatia News) correlation was found between election results and number of published articles about the candidates, the number of comments on the candidates, the number of citizen journalists who commented on the candidates and the number of citizen journalists positively or negatively oriented toward candidates. The results of this research in the cases of five croatian news portals showed that there is a relationship between participatory journalism and election results, and that conversation between citizen journalists is still far from the ideal of public deliberation that describes Habermas (1996)