Assessing public awareness of social justice documentary films based on news coverage versus social media

The comprehensive measurement of the impact that information products have on individuals, groups and society is of practical relevance to many actors, including philanthropic funding organizations. In this paper we focus on assessing one dimension of impact, namely public awareness, which we conceptualize as the amount and substance of attention that information products gain from the press and social media. We are looking at a type of products that philanthropic organizations fund, namely social justice documentaries. Using topic modeling as a text summarization technique, we find that films from certain domains, such as “Politics and Government” and “Environment and Nature,” attract more attention than productions on others, such as “Gender and Ethnicity”. We also observe that film-related public discourse on social media (Facebook and non-expert reviews) has a higher overlap with the content of a film than press coverage of films does. This is partially due to the fact that social media users focus more on the topics of a production whereas the press pays strong attention to cinematographic and related features

Kooperation der Lernorte in der beruflichen Bildung (KOLIBRI). Abschlussbericht des Programmträgers zum BLK-Programm

Der Abschlussbericht stellt den (vorläufigen) Endpunkt intensiver Forschungen zum Thema "Lernortkooperation" dar. Im Zeitraum von Oktober 1999 bis Dezember 2003 wurden 28 Modellversuche, die zum Thema Lernortkooperation arbeiteten, im Programm KOLIBRI ("Kooperation der Lernorte in der beruflichen Bildung") zusammengefasst. Die einzelnen Forschungsvorhaben untersuchten die verschiedenen Facetten von Lernortkooperation und konzipierten praktische Lösungen für die unterschiedlichsten Probleme. (DIPF/Orig.

Small decisions with big impact on data analytics

Big social data have enabled new opportunities for evaluating the applicability of social science theories that were formulated decades ago and were often based on small- to medium-sized samples. Big Data coupled with powerful computing has the potential to replace the statistical practice of sampling and estimating effects by measuring phenomena based on full populations. Preparing these data for analysis and conducting analytics involves a plethora of decisions, some of which are already embedded in previously collected data and built tools. These decisions refer to the recording, indexing and representation of data and the settings for analysis methods. While these choices can have tremendous impact on research outcomes, they are not often obvious, not considered or not being made explicit. Consequently, our awareness and understanding of the impact of these decisions on analysis results and derived implications are highly underdeveloped. This might be attributable to occasional high levels of over-confidence in computational solutions as well as the possible yet questionable assumption that Big Data can wash out minor data quality issues, among other reasons. This article provides examples for how to address this issue. It argues that checking, ensuring and validating the quality of big social data and related auxiliary material is a key ingredient for empowering users to gain reliable insights from their work. Scrutinizing data for accuracy issues, systematically fixing them and diligently documenting these processes can have another positive side effect: Closely interacting with the data, thereby forcing ourselves to understand their idiosyncrasies and patterns, can help us to move from being able to precisely model and formally describe effects in society to also understand and explain them. </jats:p

Commoning the food system: Barriers, opportunities and resilience strategies on the case of CampiAperti, Bologna, Italy

The concept of ‘Food sovereignty’ was articulated by the global peasant movement La Via Campesina in 1994, in response to the neo-liberalisation of agriculture. Most academic research on food sovereignty focusses on the global South, and only little attention has been paid to the European peasant movement and their strategies to build food sovereignty in a context in which, according to European La Via Campesina, the EU Common Agricultural Policy is putting a small farm out of business every three minutes, and agro-industry emits one fourth of all carbon emissions in the continent. This thesis discusses the transformative potential of food production and the decommodification of foodstuff from a commons and commoning perspective. Analysing the case of CampiAperti, a producer Association in Bologna, Italy, I demonstrate multiple production systems in use-value through the lens of the peasant condition where farmers have taken ownership over the production stages of their selected craft, and through commoning have put in place an agroecological value system based on animal and labour rights. In exerting their value system, two autopoietic mechanisms were developed to assert their ecological and social boundaries from the state, capitalist system and free-riders. The first one is the participatoryguarantee-system (PGS), and the second is the collaborative price-mechanism (CPM). The PGS is instrumental to self-certifying their foodstuff, which raises the critical question of boundaries and enclosures from a commons perspective. While the CPM is used to eliminate competitive behaviour amongst producers by setting their own ‘just prices’. This mechanism is scrutinised on competition, and on the tension between guaranteeing a livelihood for farmer and the affordability of their foodstuff for consumers. Both PGS and CPM mechanism defy the capitalist logic of neo-liberalisation of the food system as well as the logics of the Common Agricultural Policy (CAP), and thus these mechanisms are strategic political tools to emancipate from the capitalist food market and are employed to self-govern their own markets. Foodstuff is evaluated as a common good, arguing that the created food system is a closed commons circuit.  Conducting fieldwork on farms, markets, and assemblies, the study addresses the possibility of materialising food sovereignty by examining production and distribution of foodstuff in usevalue. It utilises a practice-centred approach and draws on a mixed-method, multi-sited ethnographic strategy to explore how individuals take responsibility of their re/production and examines the producer’s commitment to participate in self-governing the food system through commoning. The ethnographic study is supplemented with a discourse and conversational analysis to get a deeper understanding of CampiAperti’s organisation and of their complex horizontal governance structure

PyTAIL: Interactive and Incremental Learning of NLP Models with Human in the Loop for Online Data

Online data streams make training machine learning models hard because of distribution shift and new patterns emerging over time. For natural language processing (NLP) tasks that utilize a collection of features based on lexicons and rules, it is important to adapt these features to the changing data. To address this challenge we introduce PyTAIL, a python library, which allows a human in the loop approach to actively train NLP models. PyTAIL enhances generic active learning, which only suggests new instances to label by also suggesting new features like rules and lexicons to label. Furthermore, PyTAIL is flexible enough for users to accept, reject, or update rules and lexicons as the model is being trained. Finally, we simulate the performance of PyTAIL on existing social media benchmark datasets for text classification. We compare various active learning strategies on these benchmarks. The model closes the gap with as few as 10% of the training data. Finally, we also highlight the importance of tracking evaluation metric on remaining data (which is not yet merged with active learning) alongside the test dataset. This highlights the effectiveness of the model in accurately annotating the remaining dataset, which is especially suitable for batch processing of large unlabelled corpora. PyTAIL will be available at https://github.com/socialmediaie/pytail.Comment: 9pages, 3 figures, 2 table

The refugee/migrant crisis dichotomy on twitter: A network and sentiment perspective

Media reports, political statements, and social media debates on the refugee/migrant crisis shape the ways in which people and societies respond to those displaced people arriving at their borders world wide. These current events are framed and experienced as a crisis, entering the media, capturing worldwide political attention, and producing diverse and contradictory discourses and responses. The labels “migrant” and “refugee” are frequently distinguished and conflated in traditional as well as social media when describing the same groups of people. In this paper, we focus on the simultaneous struggle over meaning, legitimization, and power in representations of the refugee crisis, through the specific lens of Twitter. The 369,485 tweets analyzed in this paper cover two days after a picture of Alan Kurdi - a three-year-old Syrian boy who drowned in the Mediterranean Sea while trying to reach Europe with his family - made global headlines and sparked wide media engagement. More specifically, we investigate the existence of the dichotomy between the “deserving” refugee versus the “undeserving” migrant, as well as the relationship between sentiment expressed in tweets, their influence, and the popularity of Twitter users involved in this dichotomous characterization of the crisis. Our results show that the Twitter debate was predominantly focused on refugee related hashtags and that those tweets containing such hashtags were more positive in tone. Furthermore, we find that popular Twitter users as well as popular tweets are characterized by less emotional intensity and slightly less positivity in the debate, contrary to prior expectations. Co-occurrence networks expose the structure underlying hashtag usage and reveal a refugee-centric core of meaning, yet divergent goals of some prominent users. As social media become increasingly prominent venues for debate over a crisis, how and why people express their opinions offer valuable insights into the nature and direction of these debates

Qualitive and quantitive mass spectrometric analysis of neuroactive substances from single insect neurons

Organisms need to constantly adapt their behavior to the changing environment as well as react towards changes in their internal state. The nervous system perceives and processes such stimuli and coordinates the corresponding reactions of the body. This system is based on regulated cell-cell communication, utilizing a wide range of different chemical signaling molecules and receptors. If one wants to fully grasp how neural circuits process, modulate and relay incoming information, then the involved neuroactive substances, their cellular distribution, temporal and quantitative dynamics have to be analyzed on single cell resolution. Single cell mass spectrometry (SCMS) allows the interrogation of chemical profiles from individual cells, including neuroactive substances such as neuropeptides and biogenic amines. Matrix assisted laser desorption/ionization – time-of-flight mass spectrometry (MALDI-TOF MS) has established itself as a fast and reliable tool for the analysis of neuropeptides from single neurons of invertebrates and vertebrates alike. However, the detection of small signaling molecules, such as biogenic monoamines, by MALDI-TOF SCMS has been challenging. Biogenic monoamines play key roles in orchestrating and modulating neural circuits, therefore a MALDI-TOF SCMS based method for their detection and quantification is highly desirable. Additionally, biogenic monoamines can be co-localized with neuropeptides. Therefore the development of a MALDI-TOF SCMS based method capable of detecting both neuroactive substances would help to reveal such overlapping expression profiles. In the current thesis, I focused on the development of a MALDI-TOF SCMS based method that allows the detection and quantification of biogenic monoamines from single somata of insect neurons. The study focused on the insect octopaminergic/tyraminergic system, with an emphasis on octopamine (OA), which is considered to be homologous to the vertebrate noradrenalin/adrenalin system. By using chemical derivatization of amine moieties of OA and tyramine (TA) and an optimized sample preparation, I was able to lower the respective detection limits to single cell concentrations. Additionally, I could show that the chemical derivatization does not interfere with the detection of neuropeptides from the same sample, hence allowing the simultaneous detection of both substance classes. Further, I could show that absolute quantification of OA and TA is possible from single cell sample volumes using isotopically labeled synthetic standards. I used the developed protocol for the qualitative and quantitative analysis of OA/TA from genetically labeled and manually microdissected somata of interneurons from the fruit fly Drosophila melanogaster. Using the newly developed approach, I analyzed intracellular OA/TA ratios, compared somatic OA titers between sexes and two different OAergic cell clusters and revealed that prolonged cooling of animals has an increasing effect on detectable OA titers in the analyzed neurons. Furthermore, I used the developed protocol to analyze changes in somatic OA titers of aggression modulating OAergic neurons from the gnathal ganglion in socially naive and experienced adult male D. melanogaster. I could show that the somatic OA titer increases in these neurons when flies had social contact with the same sex compared to naive flies, which is possibly mediated by an input from pheromone detecting gustatory receptor neurons. To my knowledge, this is the first study to report a quantified increase of a somatic biogenic monoamine titer detected directly from individual isolated neurons of intact insect brains between two behavioral states by mass spectrometric analysis. In a collaborative study, I employed the developed protocol to intracellular recorded descending dorsal unpaired median neurons from the Indian stick insect Carausius morosus and was able to confirm that these neurons contain OA and TA and thus could be OAergic. Finally, as a starting point in an effort to create a map of neuropeptidergic neurons and their repertoire of neuroactive substances in adult D. melanogaster, I was involved in the analysis of single genetically labeled neuropeptidergic neuron somata using MALDI-TOF SCMS. In summary, we could describe a total of 10 different cell types characterized by their expressed neuropeptides and their location in the CNS. Future studies will focus on analyzing these cell types towards potential co-localized aminergic transmitters using the developed protocol

Statistical Inference in a Directed Network Model with Covariates

Networks are often characterized by node heterogeneity for which nodes exhibit different degrees of interaction and link homophily for which nodes sharing common features tend to associate with each other. In this paper, we propose a new directed network model to capture the former via node-specific parametrization and the latter by incorporating covariates. In particular, this model quantifies the extent of heterogeneity in terms of outgoingness and incomingness of each node by different parameters, thus allowing the number of heterogeneity parameters to be twice the number of nodes. We study the maximum likelihood estimation of the model and establish the uniform consistency and asymptotic normality of the resulting estimators. Numerical studies demonstrate our theoretical findings and a data analysis confirms the usefulness of our model.Comment: 29 pages. minor revisio