Exploiting subjectivity classification to improve information extraction

Journal ArticleInformation extraction (IE) systems are prone to false hits for a variety of reasons and we observed that many of these false hits occur in sentences that contain subjective language (e.g., opinions, emotions, and sentiments). Motivated by these observations, we explore the idea of using subjectivity analysis to improve the precision of information extraction systems. In this paper, we describe an IE system that uses a subjective sentence classifier to filter its extractions. We experimented with several different strategies for using the subjectivity classifications, including an aggressive strategy that discards all extractions found in subjective sentences and more complex strategies that selectively discard extractions. We evaluated the performance of these different approaches on the MUC-4 terrorism data set. We found that indiscriminately filtering extractions from subjective sentences was overly aggressive, but more selective filtering strategies improved IE precision with minimal recall loss

Recognizing and organizing opinions expressed in the world press

Journal ArticleTomorrow's question answering systems will need to have the ability to process information about beliefs, opinions, and evaluations-the perspective of an agent. Answers to many simple factual questions-even yes/no questions-are affected by the perspective of the information source. For example, a questioner asking question (1) might be interested to know that, in general, sources in European and North American governments tend to answer "no" to question (1), while sources in African governments tend to answer "yes:

Learning subjective nouns using extraction pattern bootstrapping

Journal ArticleWe explore the idea of creating a subjectivity classifier that uses lists of subjective nouns learned by bootstrapping algorithms. The goal of our research is to develop a system that can distinguish subjective sentences from objective sentences. First, we use two bootstrapping algorithms that exploit extraction patterns to learn sets of subjective nouns. Then we train a Naive Bayes classifier using the subjective nouns, discourse features, and subjectivity clues identified in prior research. The bootstrapping algorithms learned over 1000 subjective nouns, and the subjectivity classifier performed well, achieving 77% recall with 81% precision

Don't Let Me Be Misunderstood: Comparing Intentions and Perceptions in Online Discussions

Discourse involves two perspectives: a person's intention in making an utterance and others' perception of that utterance. The misalignment between these perspectives can lead to undesirable outcomes, such as misunderstandings, low productivity and even overt strife. In this work, we present a computational framework for exploring and comparing both perspectives in online public discussions. We combine logged data about public comments on Facebook with a survey of over 16,000 people about their intentions in writing these comments or about their perceptions of comments that others had written. Unlike previous studies of online discussions that have largely relied on third-party labels to quantify properties such as sentiment and subjectivity, our approach also directly captures what the speakers actually intended when writing their comments. In particular, our analysis focuses on judgments of whether a comment is stating a fact or an opinion, since these concepts were shown to be often confused. We show that intentions and perceptions diverge in consequential ways. People are more likely to perceive opinions than to intend them, and linguistic cues that signal how an utterance is intended can differ from those that signal how it will be perceived. Further, this misalignment between intentions and perceptions can be linked to the future health of a conversation: when a comment whose author intended to share a fact is misperceived as sharing an opinion, the subsequent conversation is more likely to derail into uncivil behavior than when the comment is perceived as intended. Altogether, these findings may inform the design of discussion platforms that better promote positive interactions.Comment: Proceedings of The Web Conference (WWW) 202

Shared Agency with Parents for Educational Goals: Ethnic Differences and Implications for College Adjustment

This study proposed and confirmed three ways in which college students can perceive shared agency and two ways in which they can perceive non-shared agency with parents when pursuing educational goals in college. Differences and similarities were examined among participants from four ethnic backgrounds (N = 515; 67% female): East Asian American, Southeast Asian American, Filipino/Pacific Islander American, and European American. Results indicated that Asian American youth reported higher levels of non-shared agency with parents (i.e., parental directing and noninvolvement), lower levels of shared agency (i.e., parental accommodation, support, or collaboration), and poorer college adjustment compared to European Americans. However, ethnic similarities were found whereby perceived shared agency in education with parents was associated with college adjustment. Multiple mediation analyses also indicated that our model of shared and non-shared agency with parents explained differences in college adjustment between Asian and European Americans, though more strongly for comparisons between European and East Asian Americans. Our results suggest that parents continue to be important in the education of older youth but that continued directing of youth’s education in college can be maladaptive

Which resources should be used to identify RCT/CCTs for systematic reviews: a systematic review

BACKGROUND: Systematic reviewers seek to comprehensively search for relevant studies and summarize these to present the most valid estimate of intervention effectiveness. The more resources searched, the higher the yield, and thus time and costs required to conduct a systematic review. While there is an abundance of evidence to suggest how extensive a search for randomized controlled trials (RCTs) should be, it is neither conclusive nor consistent. This systematic review was conducted in order to assess the value of different resources to identify trials for inclusion in systematic reviews. METHODS: Seven electronic databases, four journals and Cochrane Colloquia were searched. Key authors were contacted and references of relevant articles screened. Included studies compared two or more sources to find RCTs or controlled clinical trials (CCTs). A checklist was developed and applied to assess quality of reporting. Data were extracted by one reviewer and checked by a second. Medians and ranges for precision and recall were calculated; results were grouped by comparison. Meta-analysis was not performed due to large heterogeneity. Subgroup analyses were conducted for: search strategy (Cochrane, Simple, Complex, Index), expertise of the searcher (Cochrane, librarian, non-librarian), and study design (RCT and CCT). RESULTS: Sixty-four studies representing 13 electronic databases met inclusion criteria. The most common comparisons were MEDLINE vs. handsearching (n = 23), MEDLINE vs. MEDLINE+handsearching (n = 13), and MEDLINE vs. reference standard (n = 13). Quality was low, particularly for the reporting of study selection methodology. Overall, recall and precision varied substantially by comparison and ranged from 0 to 100% and 0 to 99%, respectively. The trial registries performed the best with median recall of 89% (range 84, 95) and median precision of 96.5% (96, 97), although these results are based on a small number of studies. Inadequate or inappropriate indexing was the reason most cited for missing studies. Complex and Cochrane search strategies (SS) performed better than Simple SS. CONCLUSION: Multiple-source comprehensive searches are necessary to identify all RCTs for a systematic review, although indexing needs to be improved. Although trial registries demonstrated the highest recall and precision, the Cochrane SS or a Complex SS in consultation with a librarian are recommended. Continued efforts to develop CENTRAL should be supported

Without Apology: Writings on Abortion in Canada

Until the late 1960s, the authorities on abortion were for the most part men—politicians, clergy, lawyers, physicians, all of whom had an interest in regulating women’s bodies. Even today, when we hear women speak publicly about abortion, the voices are usually those of the leaders of women’s and abortion rights organizations, women who hold political office, and, on occasion, female physicians. We also hear quite frequently from spokeswomen for anti-abortion groups. Rarely, however, do we hear the voices of ordinary women—women whose lives have been in some way touched by abortion. Their thoughts typically owe more to human circumstance than to ideology, and without them, we run the risk of thinking and talking about the issue of abortion only in the abstract. Without Apology seeks to address this issue by gathering the voices of activists, feminists, and scholars as well as abortion providers and clinic support staff alongside the stories of women whose experience with abortion is more personal. With the particular aim of moving beyond the polarizing rhetoric that has characterized the issue of abortion and reproductive justice for so long, Without Apology is an engrossing and arresting account that will promote both reflection and discussion.Canada Council for the Arts Government of Canada Canada Book Fund (CFB) Government of Alberta, Alberta Media Fun