Retrieving information from microblog using pattern mining and relevance feedback

Retrieving information from Twitter is always challenging due to its large volume, inconsistent writing and noise. Most existing information retrieval (IR) and text mining methods focus on term-based approach, but suffers from the problems of terms variation such as polysemy and synonymy. This problem deteriorates when such methods are applied on Twitter due to the length limit. Over the years, people have held the hypothesis that pattern-based methods should perform better than term-based methods as it provides more context, but limited studies have been conducted to support such hypothesis especially in Twitter. This paper presents an innovative framework to address the issue of performing IR in microblog. The proposed framework discover patterns in tweets as higher level feature to assign weight for low-level features (i.e. terms) based on their distributions in higher level features. We present the experiment results based on TREC11 microblog dataset and shows that our proposed approach significantly outperforms term-based methods Okapi BM25, TF-IDF and pattern based methods, using precision, recall and F measures.

Twitter: microblog e rede social

Trata-se de uma pesquisa exploratória sobre o Twitter, um tipo rede social na Internet em formato de microblog. A questão central foi compreender a popularização do serviço, sobretudo no Brasil, e como este pode ser utilizado como ferramenta de comunicação pessoal ou, mesmo, corporativa. Este estudo preliminar foi desenvolvido por meio de pesquisa documental sobre redes sociais na Internet e pesquisa exploratória, com base em artigos publicados sobre o Twitter. A principal constatação é que a utilização das redes sociais como o Twitter para difusão de informações, sejam pessoais, sejam corporativas, utilizando-se de perfis reais e institucionais em sua divulgação, gera maior credibilidade das ações desenvolvidas, bem como estas são mais rápidas e podem ser acessadas via browser ou aplicativos que rodam em outros gadgets, como celulares ou smartphones.

Campanha eleitoral e twitter: a utilização do microblog durante o 2º turno da eleição presidencial de 2010

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Analysis and identification of spamming behaviors in Sina Weibo microblog

Spamming has been a widespread problem for social networks. In recent years there is an increasing interest in the analysis of anti-spamming for microblogs, such as Twitter. In this paper we present a systematic research on the analysis of spamming in Sina Weibo platform, which is currently a dominant microblogging service provider in China. Our research objectives are to understand the specific spamming behaviors in Sina Weibo and find approaches to identify and block spammers in Sina Weibo based on spamming behavior classifiers. To start with the analysis of spamming behaviors we devise several effective methods to collect a large set of spammer samples, including uses of proactive honeypots and crawlers, keywords based searching and buying spammer samples directly from online merchants. We processed the database associated with these spammer samples and interestingly we found three representative spamming behaviors: Aggressive advertising, repeated duplicate reposting and aggressive following. We extract various features and compare the behaviors of spammers and legitimate users with regard to these features. It is found that spamming behaviors and normal behaviors have distinct characteristics. Based on these findings we design an automatic online spammer identification system. Through tests with real data it is demonstrated that the system can effectively detect the spamming behaviors and identify spammers in Sina Weibo.

Predicting Academic Performance Based on Students' Blog and Microblog Posts

This study investigates the degree to which textual complexity indices applied on students’ online contributions, corroborated with a longitudinal analysis performed on their weekly posts, predict academic performance. The source of student writing consists of blog and microblog posts, created in the context of a project-based learning scenario run on our eMUSE platform. Data is collected from six student cohorts, from six consecutive installments of the Web Applications Design course, comprising of 343 students. A significant model was obtained by relying on the textual complexity and longitudinal analysis indices, applied on the English contributions of 148 students that were actively involved in the undertaken projects.

Predicting Student Performance and Differences in Learning Styles based on Textual Complexity Indices applied on Blog and Microblog Posts

Social media tools are increasingly popular in Computer Supported Collaborative Learning and the analysis of students' contributions on these tools is an emerging research direction. Previous studies have mainly focused on examining quantitative behavior indicators on social media tools. In contrast, the approach proposed in this paper relies on the actual content analysis of each student's contributions in a learning environment. More specifically, in this study, textual complexity analysis is applied to investigate how student's writing style on social media tools can be used to predict their academic performance and their learning style. Multiple textual complexity indices are used for analyzing the blog and microblog posts of 27 students engaged in a project-based learning activity. The preliminary results of this pilot study are encouraging, with several indexes predictive of student grades and/or learning styles.

Topic extraction from microblog posts using conversation structures

Conventional topic models are ineffective for topic extraction from microblog messages since the lack of structure and context among the posts renders poor message-level word co-occurrence patterns. In this work, we organize microblog posts as conversation trees based on reposting and replying relations, which enrich context information to alleviate data sparseness. Our model generates words according to topic dependencies derived from the conversation structures. In specific, we differentiate messages as leader messages, which initiate key aspects of previously focused topics or shift the focus to different topics, and follower messages that do not introduce any new information but simply echo topics from the messages that they repost or reply. Our model captures the different extents that leader and follower messages may contain the key topical words, thus further enhances the quality of the induced topics. The results of thorough experiments demonstrate the effectiveness of our proposed model.

Semi-automatic keyword based approach for FIRE 2016 Microblog Track

This paper describes our semi-automatic keyword based approach for the four topics of Information Extraction from Microblogs Posted during Disasters task at Forum for Information Retrieval Evaluation (FIRE) 2016. The approach consists three phases.

Weibo, framing, and media practices in China

This study uses frames analysis to investigate online discourses and processes of political deliberation on China’s weibo (microblog) service. It offers a comparative analysis of competing discourses surrounding the case of Wang Yue, a toddler who was ran over by two motor vehicles in Foshan, following which eighteen people passed by and ignored her plight. The study aims to understand how weibo facilitate its users to express their differences and deliberate disagreements with each other. The study found that Internet users are rational in the sense that they do not simply lean towards a dichotomised choice of ‘pro-’ or ‘anti-’ official discourse, but they are able to negotiate their moral choices by considering a wide range of social and political factors in such an emotional and morally controversial incident.

Learning in 140 characters : microblogging for professional learning

This thesis investigated how microblogging, a form of online social networking, was being employed by educators to support their professional learning. The study found that educators who participate in microblogging engage in a wide range of behaviours, with certain behaviours and activities commonly exhibited. An advantage of microblogging as a professional learning tool is its ability to link educators globally to exchange ideas from different perspectives and to share resources and teaching practices. Educators who microblog have access to relevant and timely learning that is not constrained by time or distance and can be tailored to meet their individual needs.

Detecting news topics from microblogs using sequential pattern mining

This thesis presents a sequential pattern based model (PMM) to detect news topics from a popular microblogging platform, Twitter. PMM captures key topics and measures their importance using pattern properties and Twitter characteristics. This study shows that PMM outperforms traditional term-based models, and can potentially be implemented as a decision support system. The research contributes to news detection and addresses the challenging issue of extracting information from short and noisy text.

Os usos e apropriações do Twitter no processo de construção das notícias: o caso das eleições presidenciais de 2010

As eleições 2010 entraram para a história da comunicação política como a primeira em que candidatos puderam fazer uso de outras plataformas digitais que não fossem os websites. O conteúdo divulgado pelos políticos, assessores e internautas nas redes sociais acabou sendo apropriado e noticiado pela imprensa. Esta pesquisa tem por objetivo compreender melhor como a internet, e mais precisamente o Twitter, tem interferido e alterado o modo de produção jornalística na cobertura das eleições e quais foram os efeitos nas reportagens publicadas. Para isso, buscaremos analisar como os jornais Folha de S.Paulo e O Globo fizeram uso de posts do Twitter na cobertura da campanha presidencial. Nosso intuito é avaliar se os jornais buscaram captar o comportamento dos internautas no microblo g ou se reproduziram mais os tweets dos candidatos, assessores e outras fontes notáveis. Pretendemos verificar ainda as características dos posts utilizados pelos veículos em suas matérias e notas e criar categorias que identifiquem quais assuntos que circulavam no microblog eram de interesse da imprensa.

Finding Relevant Tweets

When a user of a microblogging site authors a microblog
post or browses through a microblog post, it provides cues as to what
topic she is interested in at that point in time. Example-based search
that retrieves similar tweets given one exemplary tweet, such as the one
just authored, can help provide the user with relevant content. We investigate
various components of microblog posts, such as the associated
timestamp, author’s social network, and the content of the post, and
develop approaches that harness such factors in finding relevant tweets
given a query tweet. An empirical analysis of such techniques on real
world twitter-data is then presented to quantify the utility of the various
factors in assessing tweet relevance. We observe that content-wise similar
tweets that also contain extra information not already present in the
query, are perceived as useful. We then develop a composite technique
that combines the various approaches by scoring tweets using a dynamic
query-specific linear combination of separate techniques. An empirical
evaluation establishes the effectiveness of the composite technique, and
that it outperforms each of its constituents.

Enterprise Social Networking

Microblogging in the workplace as a functionality of Enterprise Social Networking (ESN) platforms is a relatively new phenomenon of which the use in knowledge work has not yet received much attention from research. In this cross-sectional study, I attempt to shed light on the role of microblogging in knowledge work. I identify microblogging use practices of knowledge workers on ESN platforms, and I identify its role in supporting knowledge work performance. A questionnaire is carried out among a non-representative sample of knowledge workers. The results shed light on the purposes of the microblogging messages that knowledge workers write. It also helps us find out whether microblogging supports them in performing their work. The survey is based on existing theory that supplied me with possible microblog purposes as well as theory on what the actions of knowledge workers are. The results reveal that “knowledge & news sharing”, “crowd sourcing”, “socializing & networking” and “discussion & opinion” are frequent microblog purposes. The study furthermore shows that microblogging benefits knowledge workers’ work. Microblogging seems to be a worthy addition to the existing means of communication in the workplace, and is especially useful to let knowledge, news and social contact reach a further and broader audience than it would in a situation without this social networking service.

¿Qué está sucediendo? la "twitteración" de los medios colombianos

Desde hace unos años, en la actividad periodística se han venido utilizando las nuevas herramientas que han surgido con el desarrollo de las tecnologías de la información y de la comunicación (TIC). Las distintas transformaciones no han significado una redefinición de lo que es la esencia del periodismo, pero si de la forma como los periodistas se adaptan a su trabajo, según las limitaciones y consideraciones que derivan el empleo de las tecnologías y del entorno sociocultural en la cual se encuentran. En este trabajo se analiza la manera como tres medios de información colombianos (dos de ellos versiones impresas y uno que solo se publica en internet) han estado empleando el microblog Twitter, que hoy en día es uno de los instrumentos más utilizados en las redacciones para difundir noticias rápidamente, invitar a que los usuarios complementen las informaciones, dar espacio a otras agendas temáticas y obtener información de primera mano sobre acontecimientos que no pueden ser cubiertos por los periodistas en un primer momento.