Ali Hürriyetoglu

Ali Hürriyetoglu
Koc University

MS

About

53
Publications
8,114
Reads
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271
Citations
Citations since 2017
34 Research Items
209 Citations
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20172018201920202021202220230102030405060
20172018201920202021202220230102030405060
Additional affiliations
October 2010 - October 2011
European Union Joint Research Center, Ispra Italy
Position
  • Trainee
Education
September 2008 - April 2012
Middle East Technical University
Field of study
  • Cognitive Science
September 2006 - September 2007
Technische Hochschule Mittelhessen
Field of study
  • Informatics
September 2004 - June 2008
Ege University
Field of study
  • Computer Engineering

Publications

Publications (53)
Preprint
Full-text available
The Event Causality Identification Shared Task of CASE 2022 involved two subtasks working on the Causal News Corpus. Subtask 1 required participants to predict if a sentence contains a causal relation or not. This is a supervised binary classification task. Subtask 2 required participants to identify the Cause, Effect and Signal spans per causal se...
Preprint
Full-text available
We provide a summary of the fifth edition of the CASE workshop that is held in the scope of EMNLP 2022. The workshop consists of regular papers, two keynotes, working papers of shared task participants, and task overview papers. This workshop has been bringing together all aspects of event information collection across technical and social science...
Preprint
Full-text available
We report results of the CASE 2022 Shared Task 1 on Multilingual Protest Event Detection. This task is a continuation of CASE 2021 that consists of four subtasks that are i) document classification, ii) sentence classification, iii) event sentence coreference identification, and iv) event extraction. The CASE 2022 extension consists of expanding th...
Preprint
Full-text available
We approach the classification problem as an entailment problem and apply zero-shot ranking to socio-political texts. Documents that are ranked at the top can be considered positively classified documents and this reduces the close reading time for the information extraction process. We use Transformer Language Models to get the entailment probabil...
Preprint
This paper presents an Artificial Intelligence approach to mining context and emotions related to olfactory cultural heritage narratives, in particular to fairy tales. We provide an overview of the role of smell and emotions in literature, as well as highlight the importance of olfactory experience and emotions from psychology and linguistic perspe...
Article
Full-text available
This paper presents an Artificial Intelligence approach to mining context and emotions related to olfactory cultural heritage narratives, particularly to fairy tales. We provide an overview of the role of smell and emotions in literature, as well as highlight the importance of olfactory experience and emotions from psychology and linguistic perspec...
Conference Paper
Full-text available
Despite the importance of understanding causality, corpora addressing causal relations are limited. There is a discrepancy between existing annotation guidelines of event causality and conventional causality corpora that focus more on linguistics. Many guidelines restrict themselves to include only explicit relations or clause-based arguments. Ther...
Preprint
This paper presents an Artificial Intelligence approach to mining context and emotions related to olfactory cultural heritage narratives, in particular to fairy tales. We provide an overview of the role of smell and emotions in literature, as well as highlight the importance of olfactory experience and emotions from psychology and linguistic perspe...
Preprint
Full-text available
The database creation utilized automated text processing tools that detect if a news article contains a protest event, locate protest information within the article, and extract pieces of information regarding the detected protest events. The basis of training and testing the automated tools is the GLOCON Gold Standard Corpus (GSC), which contains...
Preprint
Full-text available
Despite the importance of understanding causality, corpora addressing causal relations are limited. There is a discrepancy between existing annotation guidelines of event causality and conventional causality corpora that focus more on linguistics. Many guidelines restrict themselves to include only explicit relations or clause-based arguments. Ther...
Preprint
Full-text available
We propose a dataset for event coreference resolution, which is based on random samples drawn from multiple sources, languages, and countries. Early scholarship on event information collection has not quantified the contribution of event coreference resolution. We prepared and analyzed a representative multilingual corpus and measured the performan...
Preprint
Full-text available
This workshop is the fourth issue of a series of workshops on automatic extraction of socio-political events from news, organized by the Emerging Market Welfare Project, with the support of the Joint Research Centre of the European Commission and with contributions from many other prominent scholars in this field. The purpose of this series of work...
Article
Full-text available
We describe a gold standard corpus of protest events that comprise various local and international English language sources from various countries. The corpus contains document-, sentence-, and token-level annotations. This corpus facilitates creating machine learning models that automatically classify news articles and extract protest event-relate...
Article
What is the most optimal way of creating a gold standard corpus for training a machine learning system that is designed for automatically collecting protest information in a cross-country context? We show that creating a gold standard corpus for training and testing machine learning models on the basis of randomly chosen news articles from news arc...
Presentation
Full-text available
MA-CSSL presents the 3rd event of GLODEM Center AI & CSS Seminar Series with the talk of Erdem Yoruk, Cagri Y., Ali Hürriyetoğlu & firat duruşan, titled "Using AI for Multi-Country Automated Protest Event Collection" on Dec 3rd. Please visit https://lnkd.in/dsakkVm to register! #css #machinelearning #ai This seminar will speak about the potentials...
Preprint
In the scope of WNUT-2020 Task 2, we developed various text classification systems, using deep learning models and one using linguistically informed rules. While both of the deep learning systems outperformed the system using the linguistically informed rules, we found that through the integration of (the output of) the three systems a better perfo...
Preprint
Microblogs such as Twitter represent a powerful source of information. Part of this information can be aggregated beyond the level of individual posts. Some of this aggregated information is referring to events that could or should be acted upon in the interest of e-governance, public safety, or other levels of public interest. Moreover, a signific...
Preprint
Full-text available
We describe a gold standard corpus of protest events that comprise of various local and international sources from various countries in English. The corpus contains document, sentence, and token level annotations. This corpus facilitates creating machine learning models that automatically classify news articles and extract protest event-related inf...
Preprint
Full-text available
We present an overview of the CLEF-2019 Lab ProtestNews on Extracting Protests from News in the context of generalizable natural language processing. The lab consists of document, sentence, and token level information classification and extraction tasks that were referred as task 1, task 2, and task 3 respectively in the scope of this lab. The task...
Preprint
Full-text available
Nowadays event extraction systems mainly deal with a relatively small amount of information about temporal and modal qualifications of situations, primarily processing assertive sentences in the past tense. However, systems with a wider coverage of tense, aspect and mood can provide better analyses and can be used in a wider range of text analysis...
Preprint
Full-text available
We describe our effort on automated extraction of socio-political events from news in the scope of a workshop and a shared task we organized at Language Resources and Evaluation Conference (LREC 2020). We believe the event extraction studies in computational linguistics and social and political sciences should further support each other in order to...
Chapter
Full-text available
We present an overview of the CLEF-2019 Lab ProtestNews on Extracting Protests from News in the context of generalizable natural language processing. The lab consists of document, sentence, and token level information classification and extraction tasks that were referred as task 1, task 2, and task 3 respectively in the scope of this lab. The task...
Chapter
Full-text available
We propose a coherent set of tasks for protest information collection in the context of generalizable natural language processing. The tasks are news article classification, event sentence detection, and event extraction. Having tools for collecting event information from data produced in multiple countries enables comparative sociology and politic...
Conference Paper
Place name recognition is one of the key tasks in Information Extraction. In this paper, we tackle this task in English News from India. We first analyze the results obtained by using available tools and corpora and then train our own models to obtain better results. Most of the previous work done on entity recognition for English makes use of simi...
Conference Paper
Twitter is a social network, which contains information of the city events (concerts, festival, etc.), city problems (traffic, collision, and road incident), the news, feelings of people, etc. For these reasons, there are many studies, which use tweet data to detect useful information to support the smart city management. In this paper, the ways of...
Chapter
Given a stream of Twitter messages about an event, we investigate the predictive power of features generated from words and temporal expressions in the messages to estimate the time to event (TTE). From labeled training data average TTE values of the predictive features are learned, so that when they occur in an event-related tweet the TTE estimate...
Conference Paper
We introduce Relevancer that processes a tweet set and enables generating an automatic classifier from it. Relevancer satisfies information needs of experts during significant events. Enabling experts to combine automatic procedures with expertise is the main contribution of our approach and the added value of the tool. Even a small amount of feedb...
Conference Paper
In this paper we describe the application of our methods to humanitarian information extraction from tweets and their performance in the scope of the SMERP 2017 Data Challenge task. Detecting and extracting the (scarce) relevant information from tweet collections as precisely, completely, and rapidly as possible is of the utmost importance during n...
Article
Full-text available
We investigate what distinguishes reported dreams from other personal narratives. The continuity hypothesis, stemming from psychological dream analysis work, states that most dreams refer to a person's daily life and personal concerns, similar to other personal narratives such as diary entries. Differences between the two texts may reveal the lingu...
Conference Paper
We introduce a tool that supports knowledge workers who want to gain insights from a tweet collection, but due to time constraints cannot go over all tweets. Our system first pre-processes, de-duplicates, and clusters the tweets. The detected clusters are presented to the expert as so-called information threads. Subsequently, based on the informati...
Conference Paper
Full-text available
Sosyal medya, internet kullanıcılarının anlık ve güncel tepkilerini içerdiğinden, özellikle akıllı şehirler kavramı ve güvenlik konusunda önemli bir potansiyel içermektedir. Bu ön çalışmada, tweet verileri üzerinde olay bilgisi odaklı yer isim analizi yapılmış, elde edilen sonuçlar tartışılmış, sonuçların Akıllı Şehirler kavramına nasıl katkı sağla...
Presentation
Full-text available
Sosyal medya, internet kullanıcılarının anlık ve güncel tepkilerini içerdiğinden, özellikle akıllı şehirler kavramı ve güvenlik konusunda önemli bir potansiyel içermektedir. Bu çalışmada, tweet verileri üzerinde olay bilgisi odaklı yer isim analizi yapılmış, elde edilen sonuçlar tartışılmış, sonuçların Akıllı Şehirler kavramına nasıl katkı sağlayab...
Conference Paper
Full-text available
Citizens or visitors of a city can supply significant information with their social media posts by using mobile devices. These data can give information about complaints, touristic attractions, emergency situations etc. Social media analysis will be beneficial for smart city and smart management concept. This study is a first attempt to analyze and...
Article
Full-text available
Citizens or visitors of a city can supply significant information with their social media posts by using mobile devices. These data can give information about complaints, touristic attractions, emergency situations etc. Social media analysis will be beneficial for smart city and smart management concept. This study is a first attempt to analyze and...
Article
Full-text available
We present a method for the identi�cation of future event start dates from Twitter streams. Taking hashtags or event name expressions as query terms, the method gathers a certain number of tweets about an event and uses clues in these tweets to estimate at what date the event will start. Clues include temporal expressions with knowledge-based and a...
Conference Paper
Full-text available
We describe a system for real-time detection of security and crisis events from online news in three Balkan languages: Turkish, Romanian and Bulgarian. The system classifies the events according to a fine-grained event type set. It extracts struc-tured information from news reports, by using a blend of keyword matching and finite state grammars for...
Conference Paper
Full-text available
Given a stream of Twitter messages about an event, we investigate the predictive power of temporal expressions in the mes-sages to estimate the time to event (TTE). From labeled training data we learn av-erage TTE estimates of temporal expres-sions and combinations thereof, and de-fine basic rules to compute the time to event from temporal expressi...
Data
Given a stream of Twitter messages about an event, we investigate the predictive power of temporal expressions in the mes- sages to estimate the time to event (TTE). From labeled training data we learn av- erage TTE estimates of temporal expres- sions and combinations thereof, and de- fine basic rules to compute the time to event from temporal expr...
Conference Paper
Full-text available
Twitter has become the source of a huge user-generated content stream of short messages, known as tweets. The content of a tweet text may vary from personal status updates to advertisements. Rich metadata is readily available as well, or may be computed automatically, such as retweet counts (the number of times the tweet was re-posted by other user...
Conference Paper
Events are mainly described in textual data by domain terms, verbs, time expressions, place names and participant information. Human readers understand features and the phase of the event by decoding these signals. Textual descriptions of events change with the time of the event and with the time the event is described. Therefore, analysis of this...
Article
Full-text available
We describe and test three methods to estimate the remaining time between a series of microtexts (tweets) and the future event they refer to via a hashtag. Our system generates hourly forecasts. A linear and a local regression-based approach are applied to map hourly clusters of tweets directly onto time-to-event. To take changes over time into acc...
Article
The paper presents a semi-automatic approach to creating sentiment dictionaries in many languages. We first produced high-level gold-standard sentiment dictionaries for two languages and then translated them automatically into third languages. Those words that can be found in both target language word lists are likely to be useful because their wor...
Thesis
Full-text available
Nowadays event extraction systems mainly deal with a relatively small amount of information about temporal and modal qualifications of situations, primarily processing assertive sentences in the past tense. However, systems with a wider coverage of tense, aspect and mood can provide better analyses and can be used in a wider range of text analysis...

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Projects

Projects (2)
Project
This research project aims to identify a new welfare regime in emerging market economies and explain why it has emerged. The project will compare China, Brazil, India, Indonesia, Mexico, South Africa and Turkey to test two hypotheses: (i) emerging market economies are forming a new welfare regime that differs from liberal, corporatist and social democratic welfare regimes of the global north on the basis of extensive and decommodifying social assistance programmes (ii) the new welfare regime emerges principally as a response to the growing political power of the poor as a dual source of threat and support for governments. The project is led by Assistant Prof. Dr. Erdem Yörük and funded by the European Research Council. Horizon 2020, Excellent Science, ERC Starting Grant 2016, Project Number: 714868, Proposal Acronym: EmergingWelfare emw.ku.edu.tr
Project
http://relevancer.science.ru.nl https://bitbucket.org/hurrial/relevancer