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Using Google 5-gram data as an external source 4 , Momeni et al. ... More precisely, Figure 10 from (Momeni et al. 2018) shows execution time for different sizes of snapshots. ...arXiv:1912.07419v1 fatcat:dxsac733uvbtdiuogocvx3denq
Fast proliferation of robots in people's everyday lives during recent years calls for a profound examination of public consensus, which is the ultimate determinant of the future of this industry. This paper investigates text corpora, consisting of posts in Twitter, Google News, Bing News, and Kickstarter, over an 8 year period to quantify the public and media opinion about this emerging technology. Results demonstrate that the news platforms and the public take an overall positive position onarXiv:1905.01615v1 fatcat:gl36i5ptmfcqvd2al2t4cyx3my
more »... bots. However, there is a deviation between news coverage and people's attitude. Among various robot types, sex robots raise the fiercest debate. Besides, our evaluation reveals that the public and news media conceptualization of robotics has altered over the recent years. More specifically, a shift from the solely industrial-purposed machines, towards more social, assistive, and multi-purpose gadgets is visible.
Lecture Notes in Computer Science
Online social media systems (such as YouTube or Reddit) provide commenting features to support augmentation of social objects (e.g. video clips or news articles). Unfortunately, many comments are not useful due to the varying intentions of the authors of comments as well as the perspectives of the readers. In this paper, we present, a framework and Web-based system for adaptive faceted ranking of social media comments, which enables users to explore different facets (e.g., subjectivity ordoi:10.1007/978-3-319-16354-3_86 fatcat:aexjw2etqvexznalboc74fi2py
more »... ) and select combinations of facets in order to extract and rank comments that match their interests and are useful for them. Based on an evaluation of the framework, we find that adaptive faceted ranking shows significant improvements over prevalent ranking methods, utilized by many platforms, with respect to the users' preferences.
Many social media portals are featuring annotation functionality in order to integrate the end users' knowledge with existing digital curation processes. This facilitates extending existing metadata about digital resources. However, due to various levels of annotators' expertise, the quality of annotations can vary from excellent to vague. The evaluation and moderation of annotations (be they troll, vague, or helpful) have not been sufficiently analyzed automatically. Available approachesdoi:10.1145/2187980.2188003 dblp:conf/www/Momeni12 fatcat:mkf35v3n45benpiskv4osiumme
more »... attempt to solve the problem by using distributed moderation systems, which are influenced by factors affecting accuracy (such as imbalance voting). Despite this, we hypothesize that analyzing and exploiting both content and context dimensions of annotations may assist the automatic moderation process. In this research, we focus on leveraging the context and content features of social web annotations for semi-automatic semantic moderation. This paper describes the vision of our research, proposes an approach for semi-automatic semantic moderation, introduces an ongoing effort from which we collect data that can serve as a basis for evaluating our assumption, and report on lessons learned so far.
For example, we may think that we are quite active but reflecting on our lifelogging Chelsea Dobbins, Reza Rawassizadeh, and Elaheh Momeni, "Detecting Physical Activity within Lifelogs towards Preventing ... Dobbins, C, Rawassizadeh, R and Momeni, E Detecting Physical Activity within Lifelogs towards Preventing Obesity and Aid Ambient Assisted Living http://researchonline.ljmu.ac.uk/id/eprint/5044/ Article ... Additionally, the SMOTE  technique has been used to oversample the Chelsea Dobbins, Reza Rawassizadeh, and Elaheh Momeni, "Detecting Physical Activity within Lifelogs towards Preventing Obesity and ...doi:10.1016/j.neucom.2016.02.088 fatcat:7qm322p465d5xc472bhn2ixyla
Online data journalism, including visualizations and other manifestations of data stories, has seen a recent surge of interest. User comments add a dynamic, social layer to interpretation, enabling users to learn from others' observations and social interact around news issues. We present the results of a qualitative study of commenting around visualizations published on a mainstream news outlet, The Economist's Graphic Detail blog. We find that surprisingly, only 42% of the comments discussdoi:10.1145/2675133.2675207 dblp:conf/cscw/HullmanDMA15 fatcat:wx55atjsgbc2hdgxljgalgeeem
more »... visualization and/or article content. Over 60% of comments discuss matters of context, including how the issue is framed and the relation to outside data. Further, over one third of total comments provide direct critical feedback on the content of presented visualizations and text articles as well as on contextual aspects of the presentation. Our findings suggest using critical social feedback from comments in the design process, and motivate the development of more sophisticated commenting interfaces that distinguish comments by reference.
Annotations allow end users to augment digital items with information, which can then be exploited for search and retrieval. We are currently extending Europeana, a platform which links to millions of digital items in European institutions, with an annotation mechanism that exposes annotations as linked data and enriches newly created annotations with links to contextually relevant resources on the Web. In two demos we showcase how we integrated that kind of content augmentation into twodoi:10.1145/1839707.1839757 dblp:conf/i-semantics/HaslhoferMGS10 fatcat:yr2mvnydobee7prri6aihhs2pm
more »... that allow users to annotate videos and historic maps.
Elaheh Momeni contributed in designing the semantic abstraction evaluation and supported its implementation. ...doi:10.3390/s150922616 pmid:26370997 pmcid:PMC4610428 fatcat:3sp26giibfg7bnxtc2exzaatjy
Historic maps are valuable scholarly resources that record information often retained by no other written source. With the YUMA Map Annotation Tool we want to facilitate collaborative annotation for scholars studying historic maps, and allow for semantic augmentation of annotations with structured, contextually relevant information retrieved from Linked Open Data sources. We believe that the integration of Web resource linkage into the scholarly annotation process is not only relevant fordoi:10.1145/1998076.1998114 dblp:conf/jcdl/SimonHRR11 fatcat:kpcszjc6ynhgbm7apknjmltymi
more »... orative research, but can also be exploited to improve search and retrieval. In this paper, we introduce the COMPASS Experiment, an ongoing crowdsourcing effort in which we are collecting data that can serve as a basis for evaluating our assumption. We discuss the scope and setup of the experiment framework and report on lessons learned from the data collected so far.
Cultural institutions are increasingly opening up their repositories and contribute digital objects to social media platforms such as Flickr. In return they often receive user comments containing information that could be incorporated in their catalog records. Since judging the usefulness of a large number of user comments is a labor-intensive task, our aim is to provide automated support for filtering potentially useful social media comments on digital objects. In this paper, we discuss thedoi:10.1145/2467696.2467711 dblp:conf/jcdl/RoochiTHH13 fatcat:thmpgxng2rctlpbulaiz4ikfeu
more »... ion of usefulness in the context of social media comments and compare it from end-users as well as expertusers perspectives. Then we present a machine-learning approach to automatically classify comments according to their usefulness. Our approach makes use of syntactic and semantic comment features and also considers user context. We present the results of an experiment we did on user comments received in six different Flickr Commons collections. They show that a few relatively straightforward features can be used to infer useful comments with up to 89% accuracy.
This work introduces a set of scalable algorithms to identify patterns of human daily behaviors. These patterns are extracted from multivariate temporal data that have been collected from smartphones. We have exploited sensors that are available on these devices, and have identified frequent behavioral patterns with a temporal granularity, which has been inspired by the way individuals segment time into events. These patterns are helpful to both end-users and third parties who provide servicesdoi:10.1109/tkde.2016.2592527 fatcat:s53ifgwujrgqbd4srvizlexjxi
more »... ased on this information. We have demonstrated our approach on two real-world datasets and showed that our pattern identification algorithms are scalable. This scalability makes analysis on resource constrained and small devices such as smartwatches feasible. Traditional data analysis systems are usually operated in a remote system outside the device. This is largely due to the lack of scalability originating from software and hardware restrictions of mobile/wearable devices. By analyzing the data on the device, the user has the control over the data, i.e. privacy, and the network costs will also be removed.
Elaheh Momeni helped in drafting the paper and conducted the smartwatch user study. Chelsea Dobbins helped in improving text and drafting both smartphone and smartwatch user studies. ...doi:10.3390/jsan4040315 fatcat:nsqrkndcg5bfvigtatdzfak4ea
Elaheh Momeni-Ortner is a research associate at the Faculty of Computer Science of the University of Vienna. She did her PhD in Computer Science at the University of Vienna. ... The final step focuses on topic evolution of news, Kickstarter comments and articles by means of word clustering (Momeni et al. 2018) . ...doi:10.1007/s42486-020-00035-1 fatcat:gwk3fo74abewfm4hvowt74pb6i
Despite the advent of wearable devices and the proliferation of smartphones, there still is no ideal platform that can continuously sense and precisely collect all available contextual information. Ideally, mobile sensing data collection approaches should deal with uncertainty and data loss originating from software and hardware restrictions. We have conducted life logging data collection experiments from 35 users and created a rich dataset (9.26 million records) to represent the real-worldarXiv:1411.4726v3 fatcat:eaipmkyps5bqpdozqoi7t7nzfa
more »... oyment issues of mobile sensing systems. We create a novel set of algorithms to identify human behavioral motifs while considering the uncertainty of collected data objects. Our work benefits from combinations of sensors available on a device and identifies behavioral patterns with a temporal granularity similar to human time perception. Employing a combination of sensors rather than focusing on only one sensor can handle uncertainty by neglecting sensor data that is not available and focusing instead on available data. Moreover, by experimenting on two real, large datasets, we demonstrate that using a sliding window significantly improves the scalability of our algorithms, which can be used by applications for small devices, such as smartphones and wearables.
Studies in Health Technology and Informatics
Social networks are a good source for monitoring public health during the outbreak of COVID-19, these networks play an important role in identifying useful information. Objectives: This study aims to draw a comparison of the public's reaction in Twitter among the countries of West Asia (a.k.a Middle East) and North Africa in order to make an understanding of their response regarding the same global threat. Methods: 766,630 tweets in four languages (Arabic, English French, and Farsi) tweeted indoi:10.3233/shti210084 pmid:33965914 fatcat:mglrfwk6nff4xfc5nbkgnztxza
more »... arch 2020, were investigated. Results: The results indicate that the only common theme among all languages is "government responsibilities (political)" which indicates the importance of this subject for all nations. Conclusion: Although nations react similarly in some aspects, they respond differently in others and therefore, policy localization is a vital step in confronting problems such as COVID-19 pandemic.
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