Sharif Digital Repository

Twitter is among the most used microblogging and online social networking services. In Twitter, a name, phrase, or topic that is mentioned at a greater rate than others is called a «trending topic» or simply «trend». Twitter trends has shown their powerful ability in many public events, elections and market changes. Nevertheless, there has been very few works focusing on understanding the dynamics of these trending topics. In this article, we thoroughly examined the Twitter's trending topics of 2018. To this end, we accessed Twitter's trends API for the full year of 2018, and devised six criteria to evaluate our dataset. These six criteria are: lexical analysis, time to reach, trend... 

Previously, we proposed ColBERT, a humor detection model based on the general linguistic structure of humor for formal English texts. ColBERT uses BERT model to produce embeddings for the text sentences, which will be put as inputs into a parallel neural network. In this paper, we utilized the proposed model on informal Spanish texts to detect humor and rate its level. The current task has three differences compared to the original humor detection task on the ColBERT dataset: (1) rating humor is a regression task rather than binary classification, (2) texts are informal, and (3) texts are in a different language. Using our general model and without any knowledge of the Spanish language, we... 

Community Question-Answering websites, such as StackOverflow and Quora, expect users to follow specific guidelines in order to maintain content quality. These systems mainly rely on community reports for assessing contents, which has serious problems, such as the slow handling of violations, the loss of normal and experienced users' time, the low quality of some reports, and discouraging feedback to new users. Therefore, with the overall goal of providing solutions for automating moderation actions in QA websites, we aim to provide a model to predict 20 quality or subjective aspects of questions in QA websites. To this end, we used data gathered by the CrowdSource team at Google Research in... 

With thousands of new questions posted every day on popular Q&A websites, there is a need for automated and accurate software solutions to replace manual moderation. In this paper, we address the critical drawbacks of crowdsourcing moderation actions in Q&A communities and demonstrate the ability to automate moderation using the latest machine learning models. From a technical point, we propose a multi-view approach that generates three distinct feature groups that examine a question from three different perspectives: 1) question-related features extracted using a BERT-based regression model; 2) context-related features extracted using a named-entity-recognition model; and 3) general lexical... 

In recent years, community Q&A websites have attracted many users and have become reliable sources among experts from various fields. These platforms have specific rules to maintain their content quality in addition to general user agreements. Due to the vast expanse of these systems in terms of the number of users and posts, manual checking and verification of new contents by the administrators and official moderators are not feasible, and these systems require scalable solutions. In major Q&A networks, the current strategy is to use crowdsourcing with reliance on reporting systems. This strategy has serious problems, including the slow handling of violations, the loss of new and... 

With the widespread access of people to the Internet and the increasing usage of social networks in all nations, social networks have become a new source to study cultural similarities and differences. We identified major issues in traditional methods of data collection in cross-cultural studies: Difficulty in access to people from many nations, limited number of samples, negative effects of translation, positive self-enhancement illusion, and a few unreported problems. These issues are either causing difficulty to perform a cross-cultural study or have negative impacts on the validity of the final results. In this paper, we propose a framework that aims to calculate cultural distance among... 

There have been many previous works to determine the determinants of housing prices. All of these works relied on a relatively small set of data, mostly collected with the help of real estate agencies. In this work, we used web mining methods to generate a big, organized dataset from a popular national brokerage website. The dataset contains structural characteristics of more than 139,000 apartments, alongside their location and price. We provided our full dataset for the article, so that other researchers can reproduce our results or conduct further analyses. Using this dataset, we analyzed housing prices of Tehran in order to identify its major determinants. To this aim, we examine the...