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The principle of transparency as a design goal and as a discourse topic: two case studies
Get PDFTransparency was first proposed as a safeguard with reference to state organization; it later became the advocated protection of society and is now incorporated into laws and regulations to minimize the risks related to information technology. Transparency derives its metaphorical meaning from the signifier of something that can be seen through, promising to display and to understand. However, transparency is not visibility but a medium to enhance it. As such, it can influence people's interpretations and understanding of what they see. This dissertation embraces a user-centered approach when designing for transparency in information systems and digital interfaces. This approach focuses on the information recipient (i.e., the user), their language, and comprehension, to make sure that transparency is genuine and not a mere legal compliance. My first three studies focus on improving comprehension by using the information already implicit in the context when designing privacy notices. They define context in a novel way, as provided by those elements spatially and temporally surrounding the action at stake. The reason is that action, according to ethnomethodology and conversation analysis, creates a background against which the subsequent events are interpreted. The guiding hypothesis of these three studies is, therefore, that the action performed by the user on the website immediately preceding the appearance of the privacy notice can affect its comprehension. In the first two studies (N = 132, 128), following a between-participants design, I manipulated the consecutiveness of a cookie notification presented in an ad-hoc website by either preserving the sequential connection between its appearance and the users' action triggering it or broking it with a delay. I also manipulate the notice's explicitness by mentioning the trigger in its title or omitting this information. Through a final survey, I measured the participants' comprehension and experience of comprehension. Their response and time to respond were collected through the ad-hoc website. In the third study, I followed the same rationale, adding the interpretation of the notice as a dependent variable and investigating the effect of different contexts (generic action –i.e., entering the website– or specific action –i.e., downloading). Overall, the results of statistical analysis suggest that the action preceding the notice affects the identification of its cause and the interpretation of its content, whereas the explicit content of the notice does not. The variables did not influence the notice acceptance, as would be foreseen by the transparency paradox. The results show the explanatory power of good contextualization: considering the sequential context in which the notice appears seems an effective design practice to achieve genuine comprehension. In a fourth study I turned my attention to methodology, to explore a method to highlight transparency-related concerns in spontaneously expressed, real-life discourses. This endeavor still pursues a user-centered approach to transparency because it aims to access how citizens talk about transparency and create a shared ground between designers and users. The method consists of collecting in a corpus the discourses of interest and applying qualitative analysis and natural language processing techniques to: 1) assess the relevance of a certain topic in a corpus by checking the overlap between the corpus's keywords and some target passages related to the object of investigation; 2) identify the terminology the document's authors used to refer to the investigation object. The method is applied to a corpus of newspaper articles as a case study. The analysis shows that even if the newspapers articles might not directly use the term ‘transparency’ to a great extent, transparency related concerns are pervasive, and relate to the corpus core arguments as expressed by its keywords.Transparency was first proposed as a safeguard with reference to state organization; it later became the advocated protection of society and is now incorporated into laws and regulations to minimize the risks related to information technology. Transparency derives its metaphorical meaning from the signifier of something that can be seen through, promising to display and to understand. However, transparency is not visibility but a medium to enhance it. As such, it can influence people's interpretations and understanding of what they see. This dissertation embraces a user-centered approach when designing for transparency in information systems and digital interfaces. This approach focuses on the information recipient (i.e., the user), their language, and comprehension, to make sure that transparency is genuine and not a mere legal compliance. My first three studies focus on improving comprehension by using the information already implicit in the context when designing privacy notices. They define context in a novel way, as provided by those elements spatially and temporally surrounding the action at stake. The reason is that action, according to ethnomethodology and conversation analysis, creates a background against which the subsequent events are interpreted. The guiding hypothesis of these three studies is, therefore, that the action performed by the user on the website immediately preceding the appearance of the privacy notice can affect its comprehension. In the first two studies (N = 132, 128), following a between-participants design, I manipulated the consecutiveness of a cookie notification presented in an ad-hoc website by either preserving the sequential connection between its appearance and the users' action triggering it or broking it with a delay. I also manipulate the notice's explicitness by mentioning the trigger in its title or omitting this information. Through a final survey, I measured the participants' comprehension and experience of comprehension. Their response and time to respond were collected through the ad-hoc website. In the third study, I followed the same rationale, adding the interpretation of the notice as a dependent variable and investigating the effect of different contexts (generic action –i.e., entering the website– or specific action –i.e., downloading). Overall, the results of statistical analysis suggest that the action preceding the notice affects the identification of its cause and the interpretation of its content, whereas the explicit content of the notice does not. The variables did not influence the notice acceptance, as would be foreseen by the transparency paradox. The results show the explanatory power of good contextualization: considering the sequential context in which the notice appears seems an effective design practice to achieve genuine comprehension. In a fourth study I turned my attention to methodology, to explore a method to highlight transparency-related concerns in spontaneously expressed, real-life discourses. This endeavor still pursues a user-centered approach to transparency because it aims to access how citizens talk about transparency and create a shared ground between designers and users. The method consists of collecting in a corpus the discourses of interest and applying qualitative analysis and natural language processing techniques to: 1) assess the relevance of a certain topic in a corpus by checking the overlap between the corpus's keywords and some target passages related to the object of investigation; 2) identify the terminology the document's authors used to refer to the investigation object. The method is applied to a corpus of newspaper articles as a case study. The analysis shows that even if the newspapers articles might not directly use the term ‘transparency’ to a great extent, transparency related concerns are pervasive, and relate to the corpus core arguments as expressed by its keywords
Coordination between vehicles in traffic
No full textThis study belongs to the ethnomethodological tradition of identifying the everyday practices accounting for the oiled machinery of social organization and applies this approach to understanding direction light usage. We observe a set of episodes videorecorded in North-East Italy in the urban traffic. We first unpack the meaning of direction light usage from a pragmatic perspective and then test our interpretation against the cases in our collection that seem to deviate from it. We argue that direction lights’ usage works as an announcement to some road users and a request to a subset of them; in both cases, direction lights convey contextualized (indexical) coordinates about the vehicle’s prospective trajectory. We then explain the cases in which signaling is omitted and draw some implications for traffic coordination and safety
Transparency is Crucial for User-Centered AI, or is it? How this Notion Manifests in the UK Press Coverage of GPT
No full textTransparency is a core principle for a user-centered AI present in all recent regulatory initiatives. Is it equally present in the public discourse? In this study, we focus on a type of AI that reached the media, i.e., GPT. We collected a corpus of national newspaper articles published in the United Kingdom (UK) while GPT-3 was the latest version (June 2020-November 2022) and investigated whether transparency was mentioned and, if so, in which terms. We used a mixed quantitative and qualitative approach, through which articles are both parsed for word frequency and manually coded. The results show that transparency was rarely explicitly mentioned, but issues underpinning transparency were addresssed in most texts. As a follow-up of the initial study, the scant presence of the term transparency is confirmed in an additional corpus of UK national newspaper articles published since the launch of ChatGPT (November 2022 - May 2023). The implications of missing transparency as a reference for AI ethical concerns in the public discourse are discussed
How to get away with cyberattacks
No full textThe possibility that common users are successfully recruited in cyberattacks represents a considerable vulnerability because it implies that citizens can legitimize cyberattacks instead of condemning them. We propose to adopt an argumentative approach to identify which premises allow such legitimization. To showcase this approach, we created four short narratives describing cyberattacks involving generic users and covering different motives for the attacks: profit, recreation, revenge, and ideology. A sample of 16 participants read the four narratives and was afterward interviewed to express their position on the attacks described. All interview transcripts were then analyzed with an argumentative approach, and 15 premises were found to account for the different positions taken. We describe the premises, their distribution across the four narratives, and discuss the implications of this approach for cybersecurity
Sharing the Space With the “Victim” Can Increase Help Rates. A Study With Virtual Reality
Get PDFA typical protocol for the psychological study of helping behavior features two core roles: a help seeker suffering from some personal or situational emergency (often called “victim”) and a potential helper. The setting of these studies is such that the victim and the helper often share the same space. We wondered whether this spatial arrangement might affect the help rate. Thus, we designed a simple study with virtual reality in which space sharing could be manipulated. The participant plays the role of a potential helper; the victim is a humanoid located inside the virtual building. When the request for help is issued, the participant can be either in the same spatial region as the victim (the virtual building) or outside it. The effect of space was tested in two kinds of emergencies: a mere request for help and a request for help during a fire. The analysis shows that, in both kinds of emergencies, the participants were more likely to help the victim when sharing the space with it. This study suggests controlling the spatial arrangement when investigating helping behavior. It also illustrates the expediency of virtual reality to further investigate the role of space on pro-social behavior during emergencies
Privacy notices_BIT paper
No full textDatasets related to three experiments (Study1: N = 132; Study 2: N = 128; Study 3: N = 91) with anonymous data collected for a work published on Behavior & Information Technology and part of a doctoral thesis.
The datasets of the first two studies contain the following variables:
ID (participant’s ID);
Condition (experimental condition; categorical);
Explicitness (mention of the cause of the appearance of the notice in its text; dichotomous);
Consecutiveness (consecutiveness of the notice presented to the participant; dichotomous);
Reading (response to the item asking if the participant read the notice; categorical);
Reading_coded (dichotomous);
Cause (response to the item asking the cause of the appearance of the notice; categorical);
Cause_coded (dichotomous);
Topic (response to the item asking the topic of the notice; categorical);
Topic_coded (dichotomous);
Perceived_C1 (response to the first item asking the participant’s level of perceived comprehension; 5-point Likert scale from “Strongly disagree” to “Strongly agree");
Perceived_C2 (response to the second item asking the participant’s level of perceived comprehension; 5-point Likert scale from “Strongly disagree” to “Strongly agree”);
Clarity (average score of three items asking the level of clarity of the notice; 5-point Likert scale from “Strongly disagree” to “Strongly agree”);
Control (response to the item asking the participant’s sense of control over his/her data; 5-point Likert scale from “Strongly disagree” to “Strongly agree”);
Privacy_concerns (average score of five items asking the level privacy concerns; 5-point Likert scale from “Strongly disagree” to “Strongly agree”);
Response_time_sec (time elapsed from the notice appearance to the participant’s response to the notice, in seconds);
Response (participant’s response to the notice; dichotomous);
Novelty (response to the item asking whether the participant noticed differences between the notice s/he saw and the ones s/he is used to see; dichotomous);
Habits (response to the item asking the participant’s usual response to similar notice; categorical);
Gender (response to the item asking the participant’s gender; dichotomous);
Age (response to the item asking the participant’s age coded in under30/over30; dichotomous);
Education (response to the item asking the participant’s level of education coded in HighSchool/University; dichotomous);
First_language (participant’s first language).
The dataset of the third study contains the following variables:
ID (participant’s ID);
Condition (experimental condition; categorical);
Explicitness (mention of the cause of the appearance of the notice in its text; dichotomous);
Consecutiveness (consecutiveness of the notice presented to the participant; dichotomous);
Reading (response to the item asking if the participant read the notice; categorical);
Reading_coded (dichotomous);
Generic_topic_coded (correctness of the participant’s response to the open-answer item asking the topic of the notice; dichotomous);
Specific_topic (response to the item asking the specific topic of the notice; categorical);
Cause (response to the item asking the cause of the appearance of the notice; categorical);
Privacy_concerns (average score of five items asking the level privacy concerns; 5-point Likert scale from “Strongly disagree” to “Strongly agree”);
Response_time_sec (time elapsed from the notice appearance to the participant’s response to the notice, in seconds);
Response (participant’s response to the notice; dichotomous);
Novelty (response to the item asking whether the participant noticed differences between the notice s/he saw and the ones s/he is used to see; dichotomous);
Habits (response to the item asking the participant’s usual response to similar notice; categorical);
Gender (response to the item asking the participant’s gender; dichotomous);
Age (response to the item asking the participant’s age coded in under30/over30; dichotomous);
Education (response to the item asking the participant’s level of education coded in HighSchool/University; dichotomous);
First_language (participant’s first language)
Kada provjerene informacije postanu viralne: višenacionalna analiza širenja sadržaja europskih provjeravatelja informacija na Twitteru
No full textTo be effective in countering misinformation, it is paramount for fact-checkers to reach a wide audience. This study investigates the dynamics leading to broader engagement with fact-checking content published on social networks. It analyzes the dissemination activity on Twitter (later rebranded as X) of a cross-national sample of European fact-checkers over a span of four months. We employ Network Analysis and Natural Language Processing techniques (sentiment analysis and keyword extraction), to address four questions: 1. Are there specific tweets that attract the majority of engagement?; 2. Do these tweets draw engagement from audiences beyond their usual reach?; 3. What is the prevailing sentiment expressed in these tweets – positive, neutral, or negative?; 4. What topics are covered in these highly engaging tweets? Results show that certain tweets receive significantly higher engagement, extending beyond typical audience. Furthermore, our findings suggest that popular tweet topics are country-specific, and negative tweets attract more interaction in most considered countries.Kako bi se učinkovito suprotstavilo dezinformacijama, ključno je da provjeravatelji točnosti informacija (engl. fact-checkers) dosegnu široku publiku. Ovaj rad analizira dinamiku koja vodi do većeg angažmana sa sadržajem objavljenim na društvenim mrežama koji su provjeravatelji informacija provjerili. Analizirana je aktivnost širenja na Twitteru (poslije nazvanom X) uzorka europskih provjeravatelja informacija tijekom četiriju mjeseca. Korištene su tehnike analize mreža i obrade prirodnog jezika (analiza sentimenta i izdvajanje ključnih riječi) za odgovore na četiri pitanja: 1. Privlače li određeni tvitovi većinu angažmana?, 2. Privlače li ti tvitovi angažman publike izvan uobičajenog dosega?, 3. Kakav je prevladavajući sentiment u tim tvitovima – pozitivan, neutralan ili negativan? i 4. Koje teme pokrivaju ti tvitovi koji izazivaju veliki angažman? Rezultati pokazuju da određeni tvitovi dobivaju značajno veći angažman, proširujući se izvan tipične publike. Nadalje, rezultati sugeriraju da su popularne teme tvitova specifične za pojedine zemlje, a negativni tvitovi privlače više interakcija u većini razmatranih zemalja
Relevance Theory for Mapping Cognitive Biases in Fact-Checking: An Argumentative Approach
Get PDFIn the fast-paced, densely populated information landscape shaped by digitization, distinguishing information from misinformation is critical. Fact-checkers are effective in fighting fake news but face challenges such as cognitive overload and time pressure, which increase susceptibility to cognitive biases. Establishing standards to mitigate these biases can improve the quality of fact-checks, bolster audience trust, and protect against reputation attacks from disinformation actors. While previous research has focused on audience biases, we propose a novel approach grounded on relevance theory and the argumentum model of topics to identify (i) the biases intervening in the fact-checking process, (ii) their triggers, and (iii) at what level of reasoning they act. We showcase the predictive power of our approach through a multimethod case study involving a semi-automatic literature review, a fact-checking simulation with 12 news practitioners, and an online survey involving 40 journalists and fact-checkers. The study highlights the distinction between biases triggered by relevance by effort and effect, offering a taxonomy of cognitive biases and a method to map them within decision-making processes. These insights can inform trainings to enhance fact-checkers’ critical thinking skills, improving the quality and trustworthiness of fact-checking practices
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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