Harith Alani

The Open University (UK) · Knowledge Media Institute

Hate speech comes in different forms depending on the communities targeted, often based on factors like gender, sexuality, race, or religion. Detecting it online is challenging because existing systems are not accounting for the diversity of hate based on the identity of the target and may be biased towards certain groups, leading to inaccurate res...

Bias in Artificial Intelligence (AI) is a critical and timely issue due to its sociological, economic and legal impact, as decisions made by biased algorithms could lead to unfair treatment of specific individuals or groups. Multiple surveys have emerged to provide a multidisciplinary view of bias or to review bias in specific areas such as social...

With the ever growing involvement of data-driven AI-based decision making technologies in our daily social lives, the fairness of these systems is becoming a crucial phenomenon. However, an important and often challenging aspect in utilizing such systems is to distinguish validity for the range of their application especially under distribution shi...

Due to the rise in toxic speech on social media and other online platforms, there is a growing need for systems that could automatically flag or filter such content. Various supervised machine learning approaches have been proposed, trained from manually-annotated toxic speech corpora. However, annotators sometimes struggle to judge or to agree on...

How can we better mediate processes of learning at large institutions? Learning analytics are used primarily in online and blended learning environments to expose patterns in learning behaviour or interaction. They make use of digital traces from virtual learning environments and combine this with other learner data. The goal is to assist both educ...

Online community managers work towards building and managing communities around a given brand or topic. A risk imposed on such managers is that their community may die out and its utility diminish to users. Understanding what drives attention to content and the dynamics of discussions in a given community informs the community manager and/or host w...

This paper summarises work where we combined semantic web technologies with deep learning systems to obtain state-of-the art explainable misinformation detection. We proposed a conceptual and computational model to describe a wide range of misinformation detection systems based around the concepts of credibility and reviews. We described how Credib...

Correcting misconceptions and false beliefs are important for injecting reliable information about COVID-19 into public discourse, but what impact does this have on the continued proliferation of misinforming claims? Fact-checking organisations produce content with the aim of reducing misinformation spread, but our knowledge of its impact on misinf...

In the context of the Covid-19 pandemic, the consequences of misinformation are a matter of life and death. Correcting misconceptions and false beliefs are important for injecting reliable information about the outbreak. Fact-checking organisations produce content with the aim of reducing misinformation spread, but our knowledge of its impact on mi...

Artificial Intelligence (AI)‐based systems are widely employed nowadays to make decisions that have far‐reaching impact on individuals and society. Their decisions might affect everyone, everywhere, and anytime, entailing concerns about potential human rights issues. Therefore, it is necessary to move beyond traditional AI algorithms optimized for...

With misinformation being one of the biggest issues of current times, many organisations are emerging to offer verifications of information and assessments of news sources. However,it remains unclear how they relate in terms of coverage, overlap and agreement. In this paper we introduce a comparison of the assessments produced by different organisa...

The 'manosphere' has been a recent subject of feminist scholarship on the web. Serious accusations have been levied against it for its role in encouraging misogyny and violent threats towards women online, as well as for potentially radicalising lonely or disenfranchised men. Feminist scholars evidence this through a shift in the language and inter...

Social media plays a vital role in information sharing during disasters. Unfortunately, the overwhelming volume and variety of data generated on social media makes it challenging to sieve through such content manually and determine its relevancy. Most automated approaches to classify crisis data for relevancy are based on classic statistical featur...

Big tech-players have been successful in pushing the chatbots forward. Investments in the technology are growing fast, as well as the number of users and applications available. Instead of driving investments towards a successful diffusion of the technology, user-centred studies are currently chasing the popularity of chatbots. A literature analysi...

In this paper, we present electronic participatory budgeting (ePB) as a novel application domain for recommender systems. On public data from the ePB platforms of three major US cities - Cambridge, Miami and New York City-, we evaluate various methods that exploit heterogeneous sources and models of user preferences to provide personalized recommen...

Many citizens nowadays flock to social media during crises to share or acquire the latest information about the event. Due to the sheer volume of data typically circulated during such events, it is necessary to be able to efficiently filter out irrelevant posts, thus focusing attention on the posts that are truly relevant to the crisis. Current met...

Many citizens nowadays flock to social media during crises to share or acquire the latest information about the event. Due to the sheer volume of data typically circulated during such events, it is necessary to be able to efficiently filter out irrelevant posts, thus focusing attention on the posts that are truly relevant to the crisis. Current met...

Social media platforms have become key portals for sharing and consuming information during crisis situations. However, humanitarian organisations and affected communities often struggle to sieve through the large volumes of data that are typically shared on such platforms during crises to determine which posts are truly relevant to the crisis, and...

In an increasingly digital world, identifying signs of online extremism sits at the top of the priority list for counter-extremist agencies. Researchers and governments are investing in the creation of advanced information technologies to identify and counter extremism through intelligent large-scale analysis of online data. However, to the best of...

Misinformation has become a common part of our digital media environments and it is compromising the ability of our societies to form informed opinions. It generates misperceptions, which have affected the decision making processes in many domains, including economy, health, environment, and elections, among others. Misinformation and its generatio...

Climate change is one of the biggest challenges humanity faces today. Despite of high investments in technology, battling climate change is futile without the participation of the public, and changing their perception and habits. Collective intelligence tools can play an important role in translating this “distant” concept that is climate change in...

When crises hit, many flog to social media to share or consume information related to the event. Social media posts during crises tend to provide valuable reports on affected people, donation offers, help requests, advice provision, etc. Automatically identifying the category of information (e.g., reports on affected individuals, donations and volu...

Whilst a significant body of learning analytics research tends to focus on impact from the perspective of usability or improved learning outcomes, this paper proposes an approach based on Affordance Theory to describe awareness and intention as a bridge between usability and impact. 10 educators at 3 European institutions participated in detailed i...

Police forces in the UK make use of social media to communicate and engage with the public. However, while guidance reports claim that social media can enhance the accessibility of policing organisations, research studies have shown that exchanges between the citizens and the police tend to be infrequent. Social media usually act as an extra channe...

From its start, the so-called Islamic State of Iraq and the Levant (ISIL/ISIS) has been successfully exploiting social media networks, most notoriously Twitter, to promote its propaganda and recruit new members, resulting in thousands of social media users adopting a pro-ISIS stance every year. Automatic identification of pro-ISIS users on social m...

Sentiment analysis over social streams offers governments and organisations a fast and effective way to monitor the publics' feelings towards policies, brands, business, etc. General purpose sentiment lexicons have been used to compute sentiment from social streams, since they are simple and effective. They calculate the overall sentiment of texts...

Conserving fossil-based energy to reduce carbon emissions is key to slowing down global warming. The 2015 Paris agreement on climate change emphasised the importance of raising public awareness and participation to address this societal challenge. In this paper we introduce EnergyUse; a collective platform for raising awareness on climate change, b...

The Climate Challenge is an online application in the tradition of games with a purpose that combines practical steps to reduce carbon footprint with predictive tasks to estimate future climate-related conditions. As part of the Collective Awareness Platform, the application aims to increase environmental literacy and motivate users to adopt more s...

Characterising social media topics often requires new features to be continuously taken into account, and thus increasing the need for classifier retraining. One challenging aspect is the emergence of ambiguous features, which can affect classification performance. In this paper we investigate the impact of the use of ambiguous features in a topic...

Sentiment analysis over social streams offers governments and organisations a fast and effective way to monitor the publics’ feelings towards policies, brands, business, etc. In this paper we present SentiCircles, a platform that captures feedback from social media conversations and applies contextual and conceptual sentiment analysis models to ext...

While individual behaviour change is considered a central strategy to mitigate climate change, public engagement is still limited. Aiming to raise awareness, and to promote behaviour change, governments and organisations are conducting multiple pro-environmental campaigns, particularly via social media. However, to the best of our knowledge, these...

Nowadays, Question Answering (Q&A) websites are popular source of information for finding answers to all kind of questions. Due to this popularity it is critical to help the identification of best answers to existing questions for simplifying the access to relevant information. Although it is possible to identify relatively accurately best answers...

Addressing the challenge of engaging people with climate change, this paper sheds light on the Climate Challenge, a crowdsourcing application in the tradition of games with purpose that relies on different strategies for informing and inviting users to adopt sustainable lifestyle choices. Towards building an extensive perspective of engagement, we...

Social media is a common place for people to post and share digital reflections of their life events, including major events such as getting married, having children, graduating, etc. Although the creation of such posts is straightforward, the identification of events on online media remains a challenge. Much research in recent years focused on ext...

The value of Question Answering (Q&A) communities is dependent on members of the community finding the questions they are most willing and able to answer. This can be difficult in communities with a high volume of questions. Much previous has work attempted to address this problem by recommending questions similar to those already answered. However...

New social media has led to an explosion in personal digital data that encompasses both those expressions of self chosen by the individual as well as reflections of self provided by other, third parties. The resulting Digital Personhood (DP) data is complex and for many users it is too easy to become lost in the mire of digital data. This paper stu...

Value of online Question Answering (Q&A) communities is driven by the question-answering behaviour of its members. Finding the questions that members are willing to answer is therefore vital to the efficient operation of such communities. In this paper, we aim to identify the parameters that correlate with such behaviours. We train different models...

Sentiment analysis on Twitter has attracted much attention recently due to its wide applications in both, commercial and public sectors. In this paper we present SentiCircles, a lexicon-based approach for sentiment analysis on Twitter. Different from typical lexicon-based approaches, which offer a fixed and static prior sentiment polarities of word...

Online paedophile activity in social media has become a major concern in society as Internet access is easily available to a broader younger population. One common form of online child exploitation is child grooming, where adults and minors exchange sexual text and media via social media platforms. Such behaviour involves a number of stages perform...

Social media has become a prime place where many users announce their personal events, such as getting married, graduating, or having a baby, to name a few. It is common for users to post about such events and receive attention from their friends. Such events are often sought after by social platforms to enrich users timelines, to create life-log v...

Social Media is commonly used by policing organisations to spread the word on crime, weather, missing person, etc. In this work we aim to understand what attracts citizens to engage with social media policing content. To study these engagement dynamics we propose a combination of machine learning and semantic analysis techniques. Our initial resear...

Social media has become an effective channel for communicating both trends and public opinion on current events. However the automatic topic classification of social media content pose various challenges. Topic classification is a common technique used for automatically capturing themes that emerge from social media streams. However, such technique...

DBpedia has become one of the major sources of structured knowledge extracted from Wikipedia. Such structures gradually re-shape the representation of Topics as new events relevant to such topics emerge. Such changes make evident the continuous evolution of topic representations and introduce new challenges to supervised topic classification tasks,...

Most existing approaches to Twitter sentiment analysis assume that sentiment is explicitly expressed through affective words. Nevertheless, sentiment is often implicitly expressed via latent semantic relations, patterns and dependencies among words in tweets. In this paper, we propose a novel approach that automatically captures patterns of words o...

Governmental policy makers can use social networking sites to better engage with citizens. On the one hand social networking sites are well accepted by citizens and a familiar environment where discussions are already taking place and social networking sites are also more important for politicians. Thus, a need for information retrieval (the policy...

Understanding what attracts users to engage with social media content (i.e. reply-to, share, favourite) is important in domains such as market analytics, advertising, and community management. To date, many pieces of work have examined engagement dynamics in isolated platforms with little consideration or assessment of how these dynamics might vary...

Several studies and official reports argue that changing people's behavior towards energy consumption is a vital part of our fight against climate change. Engaging people into this issue is the first step towards a social change. However, it has been shown that information campaigns and technology alone are insufficient to achieve such engagement....

Sentiment classification over Twitter is usually affected by the noisy nature (abbreviations, irregular forms) of tweets data. A popular procedure to reduce the noise of textual data is to remove stopwords by using pre-compiled stopword lists or more sophisticated methods for dynamic stopword identification. However, the effectiveness of removing s...

Lexicon-based approaches to Twitter sentiment analysis are gaining much popularity due to their simplicity, domain independence, and relatively good performance. These approaches rely on sentiment lexicons, where a collection of words are marked with fixed sentiment polarities. However, words’ sentiment orientation (positive, neural, negative) and/...

Sentiment lexicons for sentiment analysis offer a simple, yet effective way to obtain the prior sentiment information of opinionated words in texts. However, words’ sentiment orientations and strengths often change throughout various contexts in which the words appear. In this paper, we propose a lexicon adaptation approach that uses the contextual...

Sentiment lexicons for sentiment analysis offer a simple, yet effective way to obtain the prior sentiment information of opinionated words in texts. However, words' sentiment orientations and strengths often change throughout various contexts in which the words appear. In this paper, we propose a lexicon adaptation approach that uses the contextual...

Universities strive to collect feedback from students to improve their courses and tutorship. Such feedback is often collected at the end of a course via survey forms. However, such methods in collecting feedback are too controlled, slow, and passive. With the rise of social media, many students are finding online venues to group and share their ex...

With the rise of social networking sites user information is becoming increasingly complex and sophisticated. The needs, behaviours and preferences of users are dynamically changing, depending on their background knowledge, their current task, and many other parameters. Existing ontology models capture demographic information as well as the users'...

Creating video clips out of personal content from social media is on the rise. MuseumOfMe, Facebook Lookback, and Google Awesome are some popular examples. One core challenge to the creation of such life summaries is the identification of personal events, and their time frame. Such videos can greatly benefit from automatically distinguishing betwee...

Sentiment analysis over Twitter offers organisations and indi-viduals a fast and effective way to monitor the publics' feelings towards them and their competitors. To assess the performance of sentiment analysis methods over Twitter a small set of evaluation datasets have been released in the last few years. In this paper we present an overview of...

For community managers and hosts it is not only important to identify the current key topics of a community but also to assess the specificity level of the community for: a) creating sub-communities, and: b) anticipating community behaviour and topical evolution. In this paper we present an approach that empirically characterises the topical specif...

Online communities provide a useful environment for web users to communicate and interact with other users by sharing their thoughts, ideas and opinions, and for resolving problems and issues. Companies and organisations now host online communities in order to support their products and services. Given this investment such communities are required...