This study examines the extent of the gap between the proportions of survey respondents reporting (1) having the possibility to use and (2) using special transport services (STS) compared to the corresponding gaps for other transport modes. For persons eligible for STS, differences between those who use them and those who do not use them are explored. The frequencies with which these two groups leave the home are then compared. Those aged 65-69, those with higher self-rated health and those cohabiting were less likely to use STS, despite being eligible. Those using STS tend to leave the home less often.
{"title":"Examining the Use and Non-use of Special Transport Services in Sweden’s Large City-Regions: The Last Resort?","authors":"Jean Ryan, M. Zingmark","doi":"10.32866/001c.49873","DOIUrl":"https://doi.org/10.32866/001c.49873","url":null,"abstract":"This study examines the extent of the gap between the proportions of survey respondents reporting (1) having the possibility to use and (2) using special transport services (STS) compared to the corresponding gaps for other transport modes. For persons eligible for STS, differences between those who use them and those who do not use them are explored. The frequencies with which these two groups leave the home are then compared. Those aged 65-69, those with higher self-rated health and those cohabiting were less likely to use STS, despite being eligible. Those using STS tend to leave the home less often.","PeriodicalId":73025,"journal":{"name":"Findings (Sydney (N.S.W.)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41575956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The increase in the availability of GPS-based movement data has enabled the exploration of mobility patterns in urban transportation networks. Understanding the relationship between social vulnerability and transportation flows from big data during natural disasters is crucial for utilities and policymakers for decision-making purposes, such as evacuation and restoration planning. In this study, we explore the geographic variation of changes in trip times of taxi trips in New York City (NYC) before and after Hurricane Sandy (2012) using GPS trajectory data in relation to the underlying socio-economic distribution of impacted populations using localized regression technique with GWR. The findings reveal how the spatial patterns of trip change times with respect to SVI, income levels and population density in NYC.
{"title":"Effect of Social Vulnerability on Taxi Trip Times during Hurricane Sandy","authors":"Avipsa Roy, B. Kar","doi":"10.32866/001c.53070","DOIUrl":"https://doi.org/10.32866/001c.53070","url":null,"abstract":"The increase in the availability of GPS-based movement data has enabled the exploration of mobility patterns in urban transportation networks. Understanding the relationship between social vulnerability and transportation flows from big data during natural disasters is crucial for utilities and policymakers for decision-making purposes, such as evacuation and restoration planning. In this study, we explore the geographic variation of changes in trip times of taxi trips in New York City (NYC) before and after Hurricane Sandy (2012) using GPS trajectory data in relation to the underlying socio-economic distribution of impacted populations using localized regression technique with GWR. The findings reveal how the spatial patterns of trip change times with respect to SVI, income levels and population density in NYC.","PeriodicalId":73025,"journal":{"name":"Findings (Sydney (N.S.W.)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43189379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Studies increasingly examine individual exposure to air pollution while accounting for person-specific activity-travel patterns. Supporting policymakers and local communities using the resulting data requires transparent and ethical communication of exposure levels to affected individuals and other stakeholders. This paper asks how an interactive online dashboard might represent individual-level air pollution exposure profiles to different audiences while respecting individuals’ geoprivacy. Using data from 37 Oxford (UK) residents, it shows that heterogeneous individual-level exposure profiles can be shared ethically through different combinations of visualisation method, spatial and temporal resolution of data representation and Geomasking techniques for different dashboard user groups.
{"title":"An Online Interactive Dashboard to Explore Personal Exposure to Air Pollution","authors":"W. Lee, Kayla Schulte, T. Schwanen","doi":"10.32866/001c.49875","DOIUrl":"https://doi.org/10.32866/001c.49875","url":null,"abstract":"Studies increasingly examine individual exposure to air pollution while accounting for person-specific activity-travel patterns. Supporting policymakers and local communities using the resulting data requires transparent and ethical communication of exposure levels to affected individuals and other stakeholders. This paper asks how an interactive online dashboard might represent individual-level air pollution exposure profiles to different audiences while respecting individuals’ geoprivacy. Using data from 37 Oxford (UK) residents, it shows that heterogeneous individual-level exposure profiles can be shared ethically through different combinations of visualisation method, spatial and temporal resolution of data representation and Geomasking techniques for different dashboard user groups.","PeriodicalId":73025,"journal":{"name":"Findings (Sydney (N.S.W.)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48898009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Using data collected from trail users in Woodbury, MN, this study applies gradient-boosting decision trees to explore the nonlinear associations between trail elements and user overall satisfaction. Scenery, personal safety, and connection are the most important contributors to overall satisfaction. Several trail elements show nonlinear effects on overall satisfaction. Specifically, bumps and lighting greatly affect overall satisfaction when their performance is poor, whereas personal safety, home access to trails, and shade improve overall satisfaction when performing well. The results also showed that the city should prioritize improvements on bumps, lighting, roadway crossing, safety, and access to enhance user satisfaction effectively.
{"title":"Exploring Key Correlates of Trail Satisfaction and their Nonlinear Relationships in Suburban Areas","authors":"Jasmine Cao, Chun Yin","doi":"10.32866/001c.53105","DOIUrl":"https://doi.org/10.32866/001c.53105","url":null,"abstract":"Using data collected from trail users in Woodbury, MN, this study applies gradient-boosting decision trees to explore the nonlinear associations between trail elements and user overall satisfaction. Scenery, personal safety, and connection are the most important contributors to overall satisfaction. Several trail elements show nonlinear effects on overall satisfaction. Specifically, bumps and lighting greatly affect overall satisfaction when their performance is poor, whereas personal safety, home access to trails, and shade improve overall satisfaction when performing well. The results also showed that the city should prioritize improvements on bumps, lighting, roadway crossing, safety, and access to enhance user satisfaction effectively.","PeriodicalId":73025,"journal":{"name":"Findings (Sydney (N.S.W.)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42829781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-15DOI: 10.48550/arXiv.2210.08174
Jinming Zhao, Gholamreza Haffar, Ehsan Shareghi
Training end-to-end speech translation (ST) systems requires sufficiently large-scale data, which is unavailable for most language pairs and domains. One practical solution to the data scarcity issue is to convert text-based machine translation (MT) data to ST data via text-to-speech (TTS) systems.Yet, using TTS systems can be tedious and slow. In this work, we propose SpokenVocab, a simple, scalable and effective data augmentation technique to convert MT data to ST data on-the-fly. The idea is to retrieve and stitch audio snippets, corresponding to words in an MT sentence, from a spoken vocabulary bank. Our experiments on multiple language pairs show that stitched speech helps to improve translation quality by an average of 1.83 BLEU score, while performing equally well as TTS-generated speech in improving translation quality. We also showcase how SpokenVocab can be applied in code-switching ST for which often no TTS systems exit.
{"title":"Generating Synthetic Speech from SpokenVocab for Speech Translation","authors":"Jinming Zhao, Gholamreza Haffar, Ehsan Shareghi","doi":"10.48550/arXiv.2210.08174","DOIUrl":"https://doi.org/10.48550/arXiv.2210.08174","url":null,"abstract":"Training end-to-end speech translation (ST) systems requires sufficiently large-scale data, which is unavailable for most language pairs and domains. One practical solution to the data scarcity issue is to convert text-based machine translation (MT) data to ST data via text-to-speech (TTS) systems.Yet, using TTS systems can be tedious and slow. In this work, we propose SpokenVocab, a simple, scalable and effective data augmentation technique to convert MT data to ST data on-the-fly. The idea is to retrieve and stitch audio snippets, corresponding to words in an MT sentence, from a spoken vocabulary bank. Our experiments on multiple language pairs show that stitched speech helps to improve translation quality by an average of 1.83 BLEU score, while performing equally well as TTS-generated speech in improving translation quality. We also showcase how SpokenVocab can be applied in code-switching ST for which often no TTS systems exit.","PeriodicalId":73025,"journal":{"name":"Findings (Sydney (N.S.W.)","volume":"1 1","pages":"1930-1936"},"PeriodicalIF":0.0,"publicationDate":"2022-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48791652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-13DOI: 10.48550/arXiv.2210.07362
Chia-Chien Hung, Anne Lauscher, Dirk Hovy, Simone Paolo Ponzetto, Goran Glavavs
Demographic factors (e.g., gender or age) shape our language. Previous work showed that incorporating demographic factors can consistently improve performance for various NLP tasks with traditional NLP models. In this work, we investigate whether these previous findings still hold with state-of-the-art pretrained Transformer-based language models (PLMs). We use three common specialization methods proven effective for incorporating external knowledge into pretrained Transformers (e.g., domain-specific or geographic knowledge). We adapt the language representations for the demographic dimensions of gender and age, using continuous language modeling and dynamic multi-task learning for adaptation, where we couple language modeling objectives with the prediction of demographic classes. Our results, when employing a multilingual PLM, show substantial gains in task performance across four languages (English, German, French, and Danish), which is consistent with the results of previous work. However, controlling for confounding factors – primarily domain and language proficiency of Transformer-based PLMs – shows that downstream performance gains from our demographic adaptation do not actually stem from demographic knowledge. Our results indicate that demographic specialization of PLMs, while holding promise for positive societal impact, still represents an unsolved problem for (modern) NLP.
{"title":"Can Demographic Factors Improve Text Classification? Revisiting Demographic Adaptation in the Age of Transformers","authors":"Chia-Chien Hung, Anne Lauscher, Dirk Hovy, Simone Paolo Ponzetto, Goran Glavavs","doi":"10.48550/arXiv.2210.07362","DOIUrl":"https://doi.org/10.48550/arXiv.2210.07362","url":null,"abstract":"Demographic factors (e.g., gender or age) shape our language. Previous work showed that incorporating demographic factors can consistently improve performance for various NLP tasks with traditional NLP models. In this work, we investigate whether these previous findings still hold with state-of-the-art pretrained Transformer-based language models (PLMs). We use three common specialization methods proven effective for incorporating external knowledge into pretrained Transformers (e.g., domain-specific or geographic knowledge). We adapt the language representations for the demographic dimensions of gender and age, using continuous language modeling and dynamic multi-task learning for adaptation, where we couple language modeling objectives with the prediction of demographic classes. Our results, when employing a multilingual PLM, show substantial gains in task performance across four languages (English, German, French, and Danish), which is consistent with the results of previous work. However, controlling for confounding factors – primarily domain and language proficiency of Transformer-based PLMs – shows that downstream performance gains from our demographic adaptation do not actually stem from demographic knowledge. Our results indicate that demographic specialization of PLMs, while holding promise for positive societal impact, still represents an unsolved problem for (modern) NLP.","PeriodicalId":73025,"journal":{"name":"Findings (Sydney (N.S.W.)","volume":"1 1","pages":"1520-1535"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48775945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-13DOI: 10.48550/arXiv.2210.07295
Mayank Mishra, Danish Contractor, Dinesh Raghu
Traditional systems designed for task oriented dialog utilize knowledge present only in structured knowledge sources to generate responses. However, relevant information required to generate responses may also reside in unstructured sources, such as documents. Recent state of the art models such as HyKnow (Gao et al., 2021b) and SEKNOW (Gao et al., 2021a) aimed at overcoming these challenges make limiting assumptions about the knowledge sources. For instance, these systems assume that certain types of information, such as a phone number, is always present in a structured knowledge base (KB) while information about aspects such as entrance ticket prices, would always be available in documents.In this paper, we create a modified version of the MutliWOZ-based dataset prepared by (Gao et al., 2021a) to demonstrate how current methods have significant degradation in performance when strict assumptions about the source of information are removed. Then, in line with recent work exploiting pre-trained language models, we fine-tune a BART (Lewiset al., 2020) based model using prompts (Brown et al., 2020; Sun et al., 2021) for the tasks of querying knowledge sources, as well as, for response generation, without makingassumptions about the information present in each knowledge source. Through a series of experiments, we demonstrate that our model is robust to perturbations to knowledge modality (source of information), and that it can fuse information from structured as well as unstructured knowledge to generate responses.
为任务导向对话设计的传统系统利用仅存在于结构化知识来源中的知识来生成响应。但是，生成响应所需的相关信息也可能驻留在非结构化源中，例如文档。最近的最先进的模型，如HyKnow (Gao等人，2021b)和SEKNOW (Gao等人，2021a)旨在克服这些挑战，对知识来源做出有限的假设。例如，这些系统假设某些类型的信息，如电话号码，总是存在于结构化知识库(KB)中，而关于某些方面的信息，如门票价格，总是在文档中可用。在本文中，我们创建了(Gao等人，2021a)准备的基于multiwoz的数据集的修改版本，以演示当删除关于信息源的严格假设时，当前方法如何显著降低性能。然后，根据最近利用预训练语言模型的工作，我们使用提示(Brown et al.， 2020;Sun et al.， 2021)用于查询知识来源的任务，以及响应生成，而无需对每个知识来源中存在的信息进行假设。通过一系列的实验，我们证明了我们的模型对知识模态(信息源)的扰动具有鲁棒性，并且它可以融合结构化和非结构化知识的信息来生成响应。
{"title":"Joint Reasoning on Hybrid-knowledge sources for Task-Oriented Dialog","authors":"Mayank Mishra, Danish Contractor, Dinesh Raghu","doi":"10.48550/arXiv.2210.07295","DOIUrl":"https://doi.org/10.48550/arXiv.2210.07295","url":null,"abstract":"Traditional systems designed for task oriented dialog utilize knowledge present only in structured knowledge sources to generate responses. However, relevant information required to generate responses may also reside in unstructured sources, such as documents. Recent state of the art models such as HyKnow (Gao et al., 2021b) and SEKNOW (Gao et al., 2021a) aimed at overcoming these challenges make limiting assumptions about the knowledge sources. For instance, these systems assume that certain types of information, such as a phone number, is always present in a structured knowledge base (KB) while information about aspects such as entrance ticket prices, would always be available in documents.In this paper, we create a modified version of the MutliWOZ-based dataset prepared by (Gao et al., 2021a) to demonstrate how current methods have significant degradation in performance when strict assumptions about the source of information are removed. Then, in line with recent work exploiting pre-trained language models, we fine-tune a BART (Lewiset al., 2020) based model using prompts (Brown et al., 2020; Sun et al., 2021) for the tasks of querying knowledge sources, as well as, for response generation, without makingassumptions about the information present in each knowledge source. Through a series of experiments, we demonstrate that our model is robust to perturbations to knowledge modality (source of information), and that it can fuse information from structured as well as unstructured knowledge to generate responses.","PeriodicalId":73025,"journal":{"name":"Findings (Sydney (N.S.W.)","volume":"1 1","pages":"1733-1742"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42413600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-13DOI: 10.48550/arXiv.2210.07188
Ankita Gupta, Marzena Karpinska, Wenlong Zhao, Kalpesh Krishna, Jack Merullo, Luke Yeh, Mohit Iyyer, Brendan T. O'Connor
Large-scale, high-quality corpora are critical for advancing research in coreference resolution. However, existing datasets vary in their definition of coreferences and have been collected via complex and lengthy guidelines that are curated for linguistic experts. These concerns have sparked a growing interest among researchers to curate a unified set of guidelines suitable for annotators with various backgrounds. In this work, we develop a crowdsourcing-friendly coreference annotation methodology, ezCoref, consisting of an annotation tool and an interactive tutorial. We use ezCoref to re-annotate 240 passages from seven existing English coreference datasets (spanning fiction, news, and multiple other domains) while teaching annotators only cases that are treated similarly across these datasets. Surprisingly, we find that reasonable quality annotations were already achievable (90% agreement between the crowd and expert annotations) even without extensive training. On carefully analyzing the remaining disagreements, we identify the presence of linguistic cases that our annotators unanimously agree upon but lack unified treatments (e.g., generic pronouns, appositives) in existing datasets. We propose the research community should revisit these phenomena when curating future unified annotation guidelines.
{"title":"ezCoref: Towards Unifying Annotation Guidelines for Coreference Resolution","authors":"Ankita Gupta, Marzena Karpinska, Wenlong Zhao, Kalpesh Krishna, Jack Merullo, Luke Yeh, Mohit Iyyer, Brendan T. O'Connor","doi":"10.48550/arXiv.2210.07188","DOIUrl":"https://doi.org/10.48550/arXiv.2210.07188","url":null,"abstract":"Large-scale, high-quality corpora are critical for advancing research in coreference resolution. However, existing datasets vary in their definition of coreferences and have been collected via complex and lengthy guidelines that are curated for linguistic experts. These concerns have sparked a growing interest among researchers to curate a unified set of guidelines suitable for annotators with various backgrounds. In this work, we develop a crowdsourcing-friendly coreference annotation methodology, ezCoref, consisting of an annotation tool and an interactive tutorial. We use ezCoref to re-annotate 240 passages from seven existing English coreference datasets (spanning fiction, news, and multiple other domains) while teaching annotators only cases that are treated similarly across these datasets. Surprisingly, we find that reasonable quality annotations were already achievable (90% agreement between the crowd and expert annotations) even without extensive training. On carefully analyzing the remaining disagreements, we identify the presence of linguistic cases that our annotators unanimously agree upon but lack unified treatments (e.g., generic pronouns, appositives) in existing datasets. We propose the research community should revisit these phenomena when curating future unified annotation guidelines.","PeriodicalId":73025,"journal":{"name":"Findings (Sydney (N.S.W.)","volume":"1 1","pages":"312-330"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45459122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Benjamin Kaufman, Ainsley Hughes, Elena Pihera, Srishti Lal
AT Local is an On Demand rideshare service operating in South Auckland, New Zealand. The service directly replaces the low patronage 371 fixed route bus and extends coverage to areas not previously served by public transport. This paper evaluates how AT Local is being used by customers located in two new catchment areas: an area in Conifer Grove and an Eastern Expansion area. Ridership analysis illustrates how AT has enabled new trip patterns. Trips from Conifer Grove are characterised by feeder service to the train network, while trips from the Eastern area fulfill feeder services while also facilitating various other trip patterns.
AT Local是一家在新西兰南奥克兰运营的按需拼车服务公司。该服务直接取代了客流量较低的371固定路线巴士，并将覆盖范围扩大到以前没有公共交通服务的地区。本文评估了位于两个新集水区的客户对AT Local的使用情况：Conifer Grove区和Eastern Expansion区。乘客量分析说明了AT是如何实现新的出行模式的。从Conifer Grove出发的旅行以向列车网络提供接驳服务为特色，而从东部地区出发的旅行则提供接驳服务，同时也促进了各种其他旅行模式。
{"title":"Electric On Demand Transit Expands Network Coverage in Auckland","authors":"Benjamin Kaufman, Ainsley Hughes, Elena Pihera, Srishti Lal","doi":"10.32866/001c.38773","DOIUrl":"https://doi.org/10.32866/001c.38773","url":null,"abstract":"AT Local is an On Demand rideshare service operating in South Auckland, New Zealand. The service directly replaces the low patronage 371 fixed route bus and extends coverage to areas not previously served by public transport. This paper evaluates how AT Local is being used by customers located in two new catchment areas: an area in Conifer Grove and an Eastern Expansion area. Ridership analysis illustrates how AT has enabled new trip patterns. Trips from Conifer Grove are characterised by feeder service to the train network, while trips from the Eastern area fulfill feeder services while also facilitating various other trip patterns.","PeriodicalId":73025,"journal":{"name":"Findings (Sydney (N.S.W.)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48286522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-13DOI: 10.48550/arXiv.2210.07206
Saif M. Mohammad
Words play a central role in how we express ourselves. Lexicons of word–emotion associations are widely used in research and real-world applications for sentiment analysis, tracking emotions associated with products and policies, studying health disorders, tracking emotional arcs of stories, and so on. However, inappropriate and incorrect use of these lexicons can lead to not just sub-optimal results, but also inferences that are directly harmful to people. This paper brings together ideas from Affective Computing and AI Ethics to present, some of the practical and ethical considerations involved in the creation and use of emotion lexicons – best practices. The goal is to provide a comprehensive set of relevant considerations, so that readers (especially those new to work with emotions) can find relevant information in one place. We hope this work will facilitate more thoughtfulness when one is deciding on what emotions to work on, how to create an emotion lexicon, how to use an emotion lexicon, how to draw meaningful inferences, and how to judge success.
{"title":"Best Practices in the Creation and Use of Emotion Lexicons","authors":"Saif M. Mohammad","doi":"10.48550/arXiv.2210.07206","DOIUrl":"https://doi.org/10.48550/arXiv.2210.07206","url":null,"abstract":"Words play a central role in how we express ourselves. Lexicons of word–emotion associations are widely used in research and real-world applications for sentiment analysis, tracking emotions associated with products and policies, studying health disorders, tracking emotional arcs of stories, and so on. However, inappropriate and incorrect use of these lexicons can lead to not just sub-optimal results, but also inferences that are directly harmful to people. This paper brings together ideas from Affective Computing and AI Ethics to present, some of the practical and ethical considerations involved in the creation and use of emotion lexicons – best practices. The goal is to provide a comprehensive set of relevant considerations, so that readers (especially those new to work with emotions) can find relevant information in one place. We hope this work will facilitate more thoughtfulness when one is deciding on what emotions to work on, how to create an emotion lexicon, how to use an emotion lexicon, how to draw meaningful inferences, and how to judge success.","PeriodicalId":73025,"journal":{"name":"Findings (Sydney (N.S.W.)","volume":"1 1","pages":"1780-1791"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48527229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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